From b09e2ad7cbb302e97b4b7d2eb20845143ad675d6 Mon Sep 17 00:00:00 2001 From: JBGruber Date: Mon, 26 Feb 2018 19:07:50 +0000 Subject: [PATCH] More formatting (#113) --- manual/dna-manual.Rnw | 856 +++++++++++++++++++++++++++++++----------- manual/dna-manual.pdf | Bin 6557239 -> 6057082 bytes 2 files changed, 635 insertions(+), 221 deletions(-) diff --git a/manual/dna-manual.Rnw b/manual/dna-manual.Rnw index 39d98485..8bed017f 100755 --- a/manual/dna-manual.Rnw +++ b/manual/dna-manual.Rnw @@ -138,8 +138,8 @@ knit_hooks$set(crop=hook_pdfcrop) \FloatBarrier \pagenumbering{arabic} -This manual demonstrates how to install, set up, and use the open-source standalone software \texttt{Discourse Network Analyzer} (\dna) and its companion \R\ package \rdna\ \citep{leifeld2018rdna}, which are designed for researchers using the method \textit{discourse network analysis}.% -\footnote{\textit{This manual is a work in progress and will be continuously updated during the year 2018. +This manual demonstrates how to install, set up, and use the open-source standalone software \texttt{Discourse Network Analyzer} (\dna) and its companion \R\ package \rdna\ \citep{leifeld2018rdna}, which are designed for researchers using the method \emph{discourse network analysis}.% +\footnote{\emph{This manual is a work in progress and will be continuously updated during the year 2018. See \url{https://github.com/leifeld/dna/blob/master/manual/dna-manual.pdf} for the most recent version}.} By combining content analysis and dynamic network analysis, this method can reveal the structure and dynamics of policy debates. The method comprises three basic steps: @@ -933,10 +933,13 @@ If these commands can be executed correctly, you are ready to use both \dna\ and \chapterauthor{Felix Rolf Bossner and Johannes Gruber} \FloatBarrier -After installing the program (see Chapter~\ref{chp:installation}), you can now create your first DNA database for your own research project. How you set up a DNA database will mainly depend on the needs of your personal research design---which should usually be clear before you start analysing data. Therefore, \dna\ can be customised during the creation of a new database in accordance with how you are planning to use the tool. +After installing the program (see Chapter~\ref{chp:installation}), you can now create your first DNA database for your own research project. +How you set up a DNA database will mainly depend on the needs of your personal research design---which should usually be clear before you start analysing data. +Therefore, \dna\ can be customised during the creation of a new database in accordance with how you are planning to use the tool. \section{Creating a new DNA Database}\label{sec:createnewdb} -In order to create a new DNA database file, you have to click on the index tab \code{File} (in the upper left corner of your DNA program window) and select the option \code{New DNA database} (see Figure~\ref{fig:newdb}). As a result, a new window will open (see Figure~\ref{fig:dbchoose}), in which you find a menu that provides you with a step-by-step guidance for specifying the configuration of your personal DNA database +In order to create a new DNA database file, you have to click on the index tab \code{File} (in the upper left corner of your DNA program window) and select the option \code{New DNA database} (see Figure~\ref{fig:newdb}). +As a result, a new window will open (see Figure~\ref{fig:dbchoose}), in which you find a menu that provides you with a step-by-step guidance for specifying the configuration of your personal DNA database \begin{figure} \includegraphics[frame, width=\linewidth]{04-1-newDatabase} \caption{Starting a new Database} @@ -951,7 +954,9 @@ In order to create a new DNA database file, you have to click on the index tab \ \label{fig:dbchoose} \end{figure} -Clicking on the first tab in the sidebar of this menu---\code{Database} (see Figure~\ref{fig:dbchoose})---opens a menu, which allows you to choose the file name and storage location of your database. For this first step of your set-up, DNA provides you with two options in respect to the type of database, in which your data is stored. Which of these options best fits your research project is dependent on the circumstances of your coding process: +Clicking on the first tab in the sidebar of this menu---\code{Database} (see Figure~\ref{fig:dbchoose})---opens a menu, which allows you to choose the file name and storage location of your database. +For this first step of your set-up, DNA provides you with two options in respect to the type of database, in which your data is stored. +Which of these options best fits your research project is dependent on the circumstances of your coding process: \begin{description} \item[\code{Local .dna file}] The preset option \code{Local .dna file} means that the dataset is stored in a local file (technically an SQLite file) on your PC or device. @@ -968,10 +973,15 @@ Clicking on the first tab in the sidebar of this menu---\code{Database} (see Fig \end{description} + + \subsection{Creating a Local DNA File}\label{subsec:createlocal} \begin{enumerate} -\item Click on the button \code{Browse} (see Figure~\ref{fig:dbchoose}). Now a pop-up menu---similiar to the one shown in Figure~\ref{fig:path}---should be open. -\item In this pop-up menu, you can choose the storage location of your database on your local device from the \code{Save in} slide down menu. Enter the name of your database in the field \code{File Name} and confirm your choices by pressing the \code{Save} button (see Figure~\ref{fig:path}). Now the pop-up menu will close. +\item Click on the button \code{Browse} (see Figure~\ref{fig:dbchoose}). +Now a pop-up menu---similiar to the one shown in Figure~\ref{fig:path}---should be open. +\item In this pop-up menu, you can choose the storage location of your database on your local device from the \code{Save in} slide down menu. +Enter the name of your database in the field \code{File Name} and confirm your choices by pressing the \code{Save} button (see Figure~\ref{fig:path}). +Now the pop-up menu will close. \begin{figure} \centering @@ -980,7 +990,8 @@ Clicking on the first tab in the sidebar of this menu---\code{Database} (see Fig \label{fig:path} \end{figure} -\item \textbf{Next, it is important, that you confirm your choices again by pressing the \code{Apply} button} (see Figure~\ref{fig:apply}). If you forget to press this button, you cannot create the database in the final step, because the program will report ``No database selected'' (see Figure~\ref{fig:nodb}). +\item \emph{Next, it is important, that you confirm your choices again by pressing the \code{Apply} button} (see Figure~\ref{fig:apply}). +If you forget to press this button, you cannot create the database in the final step, because the program will report ``No database selected'' (see Figure~\ref{fig:nodb}). \begin{figure} \includegraphics[frame, width=\linewidth]{04-5-apply} @@ -989,7 +1000,8 @@ Clicking on the first tab in the sidebar of this menu---\code{Database} (see Fig \end{figure} \end{enumerate} -If you just employ a single coder and don´t want to change or supplement the preset standard research variables (\code{person}, \code{organization}, \code{concept}, \code{agreement}) or types of codeable statements (\code{Statement}, \code{Annotation}), you can now proceed directly to the \hyperref[sec:finalstep]{final step}. If you use this manual as a beginner´s tutorial for working with \dna, however, it would be helpful to follow the steps outlined in sections~\ref{sec:userman} and \ref{sec:stattype} in order to gain a better understanding of the \dna's potential uses and its functions. +If you just employ a single coder and don´t want to change or supplement the preset standard research variables (\code{person}, \code{organization}, \code{concept}, \code{agreement}) or types of codeable statements (\code{Statement}, \code{Annotation}), you can now proceed directly to the \hyperref[sec:finalstep]{final step}. +If you use this manual as a beginner´s tutorial for working with \dna, however, it would be helpful to follow the steps outlined in sections~\ref{sec:userman} and \ref{sec:stattype} in order to gain a better understanding of the \dna's potential uses and its functions. @@ -1004,17 +1016,30 @@ Before you can configure \dna\ for working with a remote MySQL database, it is n \end{figure} \begin{enumerate} -\item You have to create a database on your MySQL server (\textit{usually by the command} \newline +\item You have to create a database on your MySQL server (\emph{usually by the command} \newline \code{CREATE DATABASE 'DatabaseName'}). -\item As you probably don´t want to allow all coders access to all other databases stored on your MySQL server, you should create distinct user profile(s) for the coding process of your \dna\ project. Even if \dna\ itself allows for -\hyperref[sec:userman]{managing multiple different coder roles}, we recommend to create separate user profiles for each of the individual coders---especially if they simultaneously edit the content of your database. It is also advisable to create passwords for the access to your database, not only for safety reasons, but also because DNA sometimes has problems with signing in users without a password. Consequently you would use the -\textbf{\code{CREATE USER 'Username'@'\%' IDENTIFIED BY 'Password'}} - command. Note, that in this step you could also restrict the respective users access to your database to a specific device by replacing '\%' through a particular server address if this is necessary. -\item Finally, you have to equip the users with the necessary rights to edit your database. In MySQL simply use -\textbf{\code{GRANT ALL PRIVILEGES ON Databasename.* TO 'Username'@'\%'}}, as it makes more sense to specify distinct user roles and rights directly in \dna\ (see~\ref{sec:userman}), where options were tailored to fit discourse network-analytical coding purposes. +\item As you probably don´t want to allow all coders access to all other databases stored on your MySQL server, you should create distinct user profile(s) for the coding process of your \dna\ project. +Even if \dna\ itself allows for +\hyperref[sec:userman]{managing multiple different coder roles}, we recommend to create separate user profiles for each of the individual coders---especially if they simultaneously edit the content of your database. +It is also advisable to create passwords for the access to your database, not only for safety reasons, but also because DNA sometimes has problems with signing in users without a password. +Consequently you would use the +\code{CREATE USER 'Username'@'\%' IDENTIFIED BY 'Password'} + command. +Note, that in this step you could also restrict the respective users access to your database to a specific device by replacing '\%' through a particular server address if this is necessary. +\item Finally, you have to equip the users with the necessary rights to edit your database. +In MySQL simply use +\code{GRANT ALL PRIVILEGES ON Databasename.* TO 'Username'@'\%'}, as it makes more sense to specify distinct user roles and rights directly in \dna\ (see~\ref{sec:userman}), where options were tailored to fit discourse network-analytical coding purposes. \end{enumerate} -Once the MySQL database is set up, you only have to select the option \code{Remote database on a server} in the first tab of the sidebar menu \code{Database} in DNA (see \fullref{sec:createnewdb}) and enter the respective username and password created in the previous step in the respective fields \code{User} and \code{Password} as well as to specify the server address of the database, with which you want to connect, in the field \code{mysql://}. If you want to access the database remotely from another device, you have to indicate the URL or IP-address of your host server, the port (which is 3306 in default, but can be \href{https://dev.mysql.com/doc/refman/5.5/en/connecting.html}{configured manually}) and the name of your database in the format \code{Hostserveraddress:Port/Databasename}. If you use DNA on the device hosting the database you can instead use the configuration shown in \textit{Figure~\ref{fig:localhost}} (\code{localhost/Databasename}). By clicking the button \code{Check} you can now check if DNA is able to connect to your database. If this is successful, you will receive the message \code{Ok. Tables will be created} \textit{(see Figure~\ref{fig:localhost})}; if not, DNA will report \code{Error: Connection could not be established}. In case of the latter, you should check the validity of your server address, username and password and---if necessary---repeat the steps outlined above. It should be noted that---for security reasons---MySQL doesn´t allow remote access with the ``root'' superuser-profile in most cases. Similar to the generation of a local .dna file, it is finally important, that you confirm your choices again by pressing the \code{Apply} button \textit{(see Figure~\ref{fig:localhost})}. If you forget to press this button, you cannot create the database in the \hyperref[sec:finalstep]{final step}, because the program will report ``No database selected'' \textit{(see Figure~\ref{fig:nodb})}. +Once the MySQL database is set up, you only have to select the option \code{Remote database on a server} in the first tab of the sidebar menu \code{Database} in DNA (see \fullref{sec:createnewdb}) and enter the respective username and password created in the previous step in the respective fields \code{User} and \code{Password} as well as to specify the server address of the database, with which you want to connect, in the field \code{mysql://}. +If you want to access the database remotely from another device, you have to indicate the URL or IP-address of your host server, the port (which is 3306 in default, but can be \href{https://dev.mysql.com/doc/refman/5.5/en/connecting.html}{configured manually}) and the name of your database in the format \code{Hostserveraddress:Port/Databasename}. +If you use DNA on the device hosting the database you can instead use the configuration shown in Figure~\ref{fig:localhost} (\code{localhost/Databasename}). +By clicking the button \code{Check} you can now check if DNA is able to connect to your database. +If this is successful, you will receive the message \code{Ok. Tables will be created} (see Figure~\ref{fig:localhost}); if not, DNA will report \code{Error: Connection could not be established}. +In case of the latter, you should check the validity of your server address, username and password and---if necessary---repeat the steps outlined above. +It should be noted that---for security reasons---MySQL doesn´t allow remote access with the ``root'' superuser-profile in most cases. +Similar to the generation of a local .dna file, it is finally important, that you confirm your choices again by pressing the \code{Apply} button (see Figure~\ref{fig:localhost}). +If you forget to press this button, you cannot create the database in the \hyperref[sec:finalstep]{final step}, because the program will report ``No database selected'' (see Figure~\ref{fig:nodb}). \begin{figure} \includegraphics[width=\linewidth]{04-7-localhost} \caption{Connecting to local MySQL database} @@ -1026,14 +1051,18 @@ Once the MySQL database is set up, you only have to select the option \code{Remo \section{User Management: Multiple Coders and Permissions}\label{sec:userman} -This second step of preparing your DNA workspace allows you to generate multiple user identities with different sets of rights for different coders. Thus, you can specify for each coder, which parts of the dataset each user can see or edit and thereby pre-structure your coding and research process. In order to do so, click on second tab \code{Coder} in the sidebar of the \code{Create new database} menu (see Figure~\ref{fig:addcoder}). +This second step of preparing your DNA workspace allows you to generate multiple user identities with different sets of rights for different coders. +Thus, you can specify for each coder, which parts of the dataset each user can see or edit and thereby pre-structure your coding and research process. +In order to do so, click on second tab \code{Coder} in the sidebar of the \code{Create new database} menu (see Figure~\ref{fig:addcoder}). \begin{figure} \includegraphics[width=\linewidth]{04-8-addcoder} \caption{Adding a second coder to the database} \label{fig:addcoder} \end{figure} -In the main window (see Figure~\ref{fig:addcoder}) you can now see a list with all coders and how many of the 12 possible actions they are permitted to perform. Now you can either add a new user profile by clicking the \code{Add} button (see Figure~\ref{fig:addcoder}) or select an existing coder and adjust her/his users rights by clicking on the user and then on the \code{Edit} button (see Figure~\ref{fig:editcoder}). Both options will open the pop-up menu shown in (see Figure~\ref{fig:coderdetail}). +In the main window (see Figure~\ref{fig:addcoder}) you can now see a list with all coders and how many of the 12 possible actions they are permitted to perform. +Now you can either add a new user profile by clicking the \code{Add} button (see Figure~\ref{fig:addcoder}) or select an existing coder and adjust her/his users rights by clicking on the user and then on the \code{Edit} button (see Figure~\ref{fig:editcoder}). +Both options will open the pop-up menu shown in (see Figure~\ref{fig:coderdetail}). \begin{figure} \includegraphics[width=\linewidth]{04-9-coderdetail} \caption{Configuring coder permissions} @@ -1042,27 +1071,48 @@ In the main window (see Figure~\ref{fig:addcoder}) you can now see a list with a This pop-up menu allows you to configure an individual profile for each coder in three simple steps: \begin{enumerate} - \item You can choose the \textbf{colour} for the coder (see Figure~\ref{fig:coderdetail}, step 1). It is recommended to choose different---if possible---divergent colours for each coder, because this permits you to detect at the first glance, which user coded which statement, as every coded statement is marked in the individual colour of its respective coder \textit{(see middle column of Figure~\ref{fig:chacoder})}. - \item You can enter the preferred name of each coder in the field \code{Name}. If possible with respect to data protection rules, it is recommended to use the real names of the coders. This makes it easier for them to select their profile (in the upper left of the main program window) the first time they start the program (see Figure~\ref{fig:chacoder}). - \item - The final step allows you to configure the \textbf{permissions} of each coder individually by (de)selecting the respective rights via a click (see Figure~\ref{fig:coderdetail}, step 3). Each new user has all of the 12 configurable permissions in the preset mode. Which parts of the dataset an individual coder should be able to see or edit, should depend on your coding process. For better orientation, a few practical implications of the 12 configurable permissions are listed below: + \item You can choose the \emph{colour} for the coder (see Figure~\ref{fig:coderdetail}, step 1). +It is recommended to choose different---if possible---divergent colours for each coder, because this permits you to detect at the first glance, which user coded which statement, as every coded statement is marked in the individual colour of its respective coder (see middle column of Figure~\ref{fig:chacoder}). + \item You can enter the preferred name of each coder in the field \code{Name}. +If possible with respect to data protection rules, it is recommended to use the real names of the coders. +This makes it easier for them to select their profile (in the upper left of the main program window) the first time they start the program (see Figure~\ref{fig:chacoder}). + \item The final step allows you to configure the \emph{permissions} of each coder individually by (de)selecting the respective rights via a click (see Figure~\ref{fig:coderdetail}, step 3). +Each new user has all of the 12 configurable permissions in the preset mode. +Which parts of the dataset an individual coder should be able to see or edit, should depend on your coding process. +For better orientation, a few practical implications of the 12 configurable permissions are listed below: \begin{description} \item[add documents] The user can add new documents (i.\,e., raw data) manually (via copy and paste or retyping) to the database $\Rightarrow$ user has (also) a research function. \item[import documents] The user can import new documents from other sources like~.txt or other~.dna files to the database or recode the metadata of multiple documents $\Rightarrow$ user has (also) a research function. - \item[delete documents] The user can delete documents from the database or dataset. This option requires at least the other permission \code{view others' documents} if the user has an organizing or editing function (structuring database for coding by other users) or the permission \code{add documents} and \code{add statements} if the coder determines own codes and organizes her/his own set of data. - \item[edit documents] The user can edit her/his own documents (i.\,e., raw data), but not necessarily the codings in these documents that were made by other users---which would require the permission \code{edit others' statements}---or the documents uploaded by other users---which requires the permission \code{edit others' documents}. This option requires at least the other permission \code{add documents} or \code{import documents} and should be selected if the user determines own codes and organizes her/his own set of data or acts as a researcher for the other coders. - \item[view others' documents] The user can view the documents uploaded by other users. This option is necessary for a collaborative coding process in which only a part of the users selects and uploads the raw data (i.\,e., documents) for all other users. The option should not be selected if each coder comes up with own codes and organizes her/his own set of data. - \item[edit others' documents] The user can edit the documents uploaded by other users. This option requires at least the other permission \code{view others' documents} and should be selected if a user organizes or edits the raw data provided by other users. - \item[add statements] The coder actually codes the data by creating and editing statements. If only a part of the users select and upload the raw data this option requires the additional permission \code{view others' documents}. If the coder suggests own codes and organizes her/his own set of data this option requires either the additional permission \code{add documents} or \code{import documents}. - \item[view others' statements] The coder can view the statements coded by other users. For example the Coder ``DNA User'' would not see the yellow statement of the Coder ``Admin'' in Figure~\ref{fig:chacoder} if this option was deselected for her/his user role. This option should be de-selected if you want to establish a blind coding process. - \item[edit others' statements] The coder can edit or correct the statements coded by other users. This option requires at least the other permission \code{view others' statements} and should only be selected for few users with an \textit{organizing}, \textit{controlling} or \textit{editing function}. - \item[add coders] The user can add new coders (see Section~\ref{sec:userman}). This option should only be selected for few users with an \textit{organizing} function. - \item[edit statement types] The user can change or complement the variables of interest (see Section~\ref{sec:stattype}). This option should only be selected for very few users or the researchers themselves because possible adjustment of these variables is usually only necessary in cases when the research design and/or research questions change fundamentally. - \item[edit regex settings] The user can specify keywords which are highlighted in the text, along with a text color (see Section~\ref{sec:regex}). For example, in \textit{Figure~\ref{fig:chacoder}} the word \code{colors} is highlighted in the raw data text (middle column), because it was specified as a keyword in the \textit{regex highlighter sidebar} in the bottom left of the DNA window. If a user does not have the right to edit the regex setting, the buttons \code{Add} and \code{Remove} in this highlighter would be hidden, but the keyword would nevertheless be visibly highlighted in the text and listed in the regex highlighter sidebar. Thus, if you specify a distinct set of theory based keywords in advance in order to render the coding procedure semi-automatic, you should not enable this option or select it only for \textit{few users}, as the respective coder could change the keywords. However, if you don't have a theoretically relevant set of keywords in advance or just specify them as a assistance for your coders, you can allow them to formulate such keywords by themselves. + \item[delete documents] The user can delete documents from the database or dataset. +This option requires at least the other permission \code{view others' documents} if the user has an organizing or editing function (structuring database for coding by other users) or the permission \code{add documents} and \code{add statements} if the coder determines own codes and organizes her/his own set of data. + \item[edit documents] The user can edit her/his own documents (i.\,e., raw data), but not necessarily the codings in these documents that were made by other users---which would require the permission \code{edit others' statements}---or the documents uploaded by other users---which requires the permission \code{edit others' documents}. +This option requires at least the other permission \code{add documents} or \code{import documents} and should be selected if the user determines own codes and organizes her/his own set of data or acts as a researcher for the other coders. + \item[view others' documents] The user can view the documents uploaded by other users. +This option is necessary for a collaborative coding process in which only a part of the users selects and uploads the raw data (i.\,e., documents) for all other users. +The option should not be selected if each coder comes up with own codes and organizes her/his own set of data. + \item[edit others' documents] The user can edit the documents uploaded by other users. +This option requires at least the other permission \code{view others' documents} and should be selected if a user organizes or edits the raw data provided by other users. + \item[add statements] The coder actually codes the data by creating and editing statements. +If only a part of the users select and upload the raw data this option requires the additional permission \code{view others' documents}. +If the coder suggests own codes and organizes her/his own set of data this option requires either the additional permission \code{add documents} or \code{import documents}. + \item[view others' statements] The coder can view the statements coded by other users. +For example the Coder ``DNA User'' would not see the yellow statement of the Coder ``Admin'' in Figure~\ref{fig:chacoder} if this option was deselected for her/his user role. +This option should be de-selected if you want to establish a blind coding process. + \item[edit others' statements] The coder can edit or correct the statements coded by other users. +This option requires at least the other permission \code{view others' statements} and should only be selected for few users with an \emph{organizing}, \emph{controlling} or \emph{editing function}. + \item[add coders] The user can add new coders (see Section~\ref{sec:userman}). +This option should only be selected for few users with an \emph{organizing} function. + \item[edit statement types] The user can change or complement the variables of interest (see Section~\ref{sec:stattype}). +This option should only be selected for very few users or the researchers themselves because possible adjustment of these variables is usually only necessary in cases when the research design and/or research questions change fundamentally. + \item[edit regex settings] The user can specify keywords which are highlighted in the text, along with a text color (see Section~\ref{sec:regex}). +For example, in Figure~\ref{fig:chacoder} the word \code{colors} is highlighted in the raw data text (middle column), because it was specified as a keyword in the \emph{regex highlighter sidebar} in the bottom left of the DNA window. +If a user does not have the right to edit the regex setting, the buttons \code{Add} and \code{Remove} in this highlighter would be hidden, but the keyword would nevertheless be visibly highlighted in the text and listed in the regex highlighter sidebar. +Thus, if you specify a distinct set of theory based keywords in advance in order to render the coding procedure semi-automatic, you should not enable this option or select it only for \emph{few users}, as the respective coder could change the keywords. +However, if you don't have a theoretically relevant set of keywords in advance or just specify them as a assistance for your coders, you can allow them to formulate such keywords by themselves. \end{description} - Please keep in mind, that every user can see and change to other user identities either accidentally or because of non-compliance, as s/he has to select her/his role the first time s/he starts the program and can change her/his role anytime \textit{(see above and Figure~\ref{fig:chacoder})} + Please keep in mind, that every user can see and change to other user identities either accidentally or because of non-compliance, as s/he has to select her/his role the first time s/he starts the program and can change her/his role anytime (see above and Figure~\ref{fig:chacoder}) \end{enumerate} \begin{figure} @@ -1077,7 +1127,10 @@ This pop-up menu allows you to configure an individual profile for each coder in \label{fig:editcoder} \end{figure} -Finally you approve your choices by clicking the \textbf{OK} button \textit{(see Figure~\ref{fig:coderdetail}, step 4)}. It is possible to change the settings either in the ``new database'' menu by selecting the respective user and clicking the \code{Edit} button (see Figure~\ref{fig:chacoder}) or changing the coder settings in the main menu. To do so, simply select a coder from the drop-down menu in the window at the top left of the main menu and then push the pencil icon underneth. The same menu as depicted in Figure~\ref{fig:chacoder} will open up again. +Finally you approve your choices by clicking the \code{OK} button (see Figure~\ref{fig:coderdetail}, step 4). +It is possible to change the settings either in the ``new database'' menu by selecting the respective user and clicking the \code{Edit} button (see Figure~\ref{fig:chacoder}) or changing the coder settings in the main menu. +To do so, simply select a coder from the drop-down menu in the window at the top left of the main menu and then push the pencil icon underneth. +The same menu as depicted in Figure~\ref{fig:chacoder} will open up again. \section{Statement Types and Variables} \label{sec:stattype} Clicking on the third tab in the sidebar of the ``Create new database'' menu---\code{Statement Types} (see Figure~\ref{fig:stattype})---opens a menu, which allows you to adjust or supplement either the variables or the types of statements, which your coders derive from the raw data. @@ -1088,7 +1141,12 @@ Clicking on the third tab in the sidebar of the ``Create new database'' menu---\ \end{figure} \subsection{Adjusting the Variables of Interest} \label{subsec:adjusvarint} -The statement type \code{DNA Statement} represents a text portion of your raw data, where an actor reveals her/his opinion/belief/etc. about an issue. Thus, the main task of your coder(s) is to identify such text portions and gain the relevant data about the actor or his opinion/belief/etc. Your research question or theory should not only dictate what kind of information should be coded as statements, but also which relevant variables of this information should be captured by the coder. As you can see in the ``Statement Types'' menu, DNAs default configuration allows capturing four variables. Selecting \code{DNA Statement} and clicking on the button \code{Edit} (see Figure~\ref{fig:stattype}) opens a pop-up window (see Figure~\ref{fig:statdetail}), which reveals the nature of this four preconfigured variables, along whose lines the coders can collect information: +The statement type \code{DNA Statement} represents a text portion of your raw data, where an actor reveals her/his opinion/belief/etc. +about an issue. +Thus, the main task of your coder(s) is to identify such text portions and gain the relevant data about the actor or his opinion/belief/etc. +Your research question or theory should not only dictate what kind of information should be coded as statements, but also which relevant variables of this information should be captured by the coder. +As you can see in the ``Statement Types'' menu, DNAs default configuration allows capturing four variables. +Selecting \code{DNA Statement} and clicking on the button \code{Edit} (see Figure~\ref{fig:stattype}) opens a pop-up window (see Figure~\ref{fig:statdetail}), which reveals the nature of this four preconfigured variables, along whose lines the coders can collect information: \begin{figure} \centering @@ -1098,36 +1156,53 @@ The statement type \code{DNA Statement} represents a text portion of your raw da \end{figure} \begin{itemize} - \item the \textbf{person} who makes the statement. - \item the \textbf{organization} the speaker is affiliated with. - \item the \textbf{concept} (opinion/belief/etc.) which is raised by the actor. - \item a dummy variable indicating whether the actor \textbf{agrees} with the concept or not. + \item the \emph{person} who makes the statement. + \item the \emph{organization} the speaker is affiliated with. + \item the \emph{concept} (opinion/belief/etc.) which is raised by the actor. + \item a dummy variable indicating whether the actor \emph{agrees} with the concept or not. \end{itemize} -Furthermore the pop-up window depicted in \textit{Figure~\ref{fig:statdetail}} shows, that each variable is assigned to a specific data type: While \code{person}, \code{organization} and \code{concept}---according to their nature as nominal variables---will be coded by a short text, \code{agreement} as a dichotomous variable will be coded as a +Furthermore the pop-up window depicted in Figure~\ref{fig:statdetail} shows, that each variable is assigned to a specific data type: While \code{person}, \code{organization} and \code{concept}---according to their nature as nominal variables---will be coded by a short text, \code{agreement} as a dichotomous variable will be coded as a \href{https://en.wikipedia.org/wiki/Boolean_data_type#Python.2C_Ruby.2C_and_JavaScript}{boolean data type} -, which accordingly only allows for two forms (either agreement or non-agreement). Neither the data type nor the name of the variables can be changed directly. However by selecting a variable and clicking on the \textbf{trash symbol} (on the right side of the \code{Add Variable} button, \textit{Figure~\ref{fig:statdetail}}, step 4) you can delete a variable and subsequently replace it by a new one. Generating a new variable---either to replace one of the preconfigured variables or because you are interested in an additional or a different set of variables---is possible in five simple steps: +, which accordingly only allows for two forms (either agreement or non-agreement). +Neither the data type nor the name of the variables can be changed directly. +However by selecting a variable and clicking on the \emph{trash symbol} (on the right side of the \code{Add Variable} button, Figure~\ref{fig:statdetail}, step 4) you can delete a variable and subsequently replace it by a new one. +Generating a new variable---either to replace one of the preconfigured variables or because you are interested in an additional or a different set of variables---is possible in five simple steps: \begin{enumerate} -\item You have to \textbf{select an existing variable} in order to activate the variable menu (see 1, Figure~\ref{fig:statdetail}). -\item Now you can enter the \textbf{name} of the new variable in the \textbf{text field} at the bottom of the pop-up window (see 2, Figure~\ref{fig:statdetail}). For example, in \textit{Figure~\ref{fig:statdetail}} we are interested in collecting the age of the person who makes the statement. Please note, that DNA does not allow spaces in variable names. Putting a space in the variable name will disable the \code{Add Variable} button necessary for step 4. -\item Now you can choose the \textbf{data type} of your variable by \textbf{clicking} on one of the \textbf{four options}. In our example, we choose the option \code{integer}, as the age of a person is neither a nominal nor a dichotomous variable, but an +\item You have to \emph{select an existing variable} in order to activate the variable menu (see 1, Figure~\ref{fig:statdetail}). +\item Now you can enter the \emph{name} of the new variable in the \emph{text field} at the bottom of the pop-up window (see 2, Figure~\ref{fig:statdetail}). +For example, in Figure~\ref{fig:statdetail} we are interested in collecting the age of the person who makes the statement. +Please note, that DNA does not allow spaces in variable names. +Putting a space in the variable name will disable the \code{Add Variable} button necessary for step 4. +\item Now you can choose the \emph{data type} of your variable by clicking on one of the four options. +In our example, we choose the option \code{integer}, as the age of a person is neither a nominal nor a dichotomous variable, but an \href{https://en.wikipedia.org/wiki/Integer_(computer_science)}{integer number}% %Should be common sense. Is link needed?% ) (see Figure~\ref{fig:statdetail}, step 3). -\item You have to click on the \code{Add-Variable} button, which has the form of a \textbf{green plus symbol} (see 4, Figure~\ref{fig:statdetail}). If this button is disabled, you probably did not select a existing variable (step 1) or have a space in your variable name (see step 2). +\item You have to click on the \code{Add-Variable} button, which has the form of a \emph{green plus symbol} (see 4, Figure~\ref{fig:statdetail}). +If this button is disabled, you probably did not select a existing variable (step 1) or have a space in your variable name (see step 2). \item Click the \code{OK} button to confirm your choices (see Figure~\ref{fig:statdetail}, step 5). \end{enumerate} -Please note, that---for the statement type ``DNA Statement''---you should only specify variables, in which you have an actual research interest in and that accordingly have to be coded for all statements by all coders. If you are interested in additional and optional information about some statements, you can specify them as variables of the other preconfigured statement type---\textbf{``Annotation''}. +Please note, that---for the statement type ``DNA Statement''---you should only specify variables, in which you have an actual research interest in and that accordingly have to be coded for all statements by all coders. +If you are interested in additional and optional information about some statements, you can specify them as variables of the other preconfigured statement type---\emph{``Annotation''}. \subsection{Adjusting the Statement Types} -There are very few research scenarios, in which it is necessary to complement the two existing types of statements with further ones or with an adjustment of type ``DNA statement''. One of them would be, if you study two parallel yet different research questions, which employ the same dataset \textit{and} the same coders at the same time. In this case, you could \textbf{first rename} the statement type ``DNA Statement'' by \textbf{selecting} it from the statement type menu, clicking the \code{Edit} button (see Figure~\ref{fig:stattype}), entering the new name (in this case: ``Statement for Research Project 1'') in the \textbf{text field on top of the pop-up window} (see Figure~\ref{fig:statdetail}) and pressing the \code{OK} button (see 5, Figure~\ref{fig:statdetail}). -Subsequently you would open a \textbf{new pop-up window} by clicking on the \code{Add} button in the statement type menu (left button in Figure~\ref{fig:stattype}). Then \textbf{name} the new statement type (in this case: ``Statement for Research Project 2'') in the text field on top of the pop-up window and \textbf{choose a color} (different from the other type) by clicking on the colored button next to this text field. Then you also need to \textbf{specify the relevant variables} synchronous to the procedure depicted in Section~\ref{subsec:adjusvarint}. -However, please evaluate carefully, if it is really neccesary for your second research interest that you specify a second statement type or if it would be possible to either conceptualize it as a variable of the existing statement type or study it sequentially or with a different set of coders (and therefore in a different \dna\ dataset). \textbf{More than two statement types (besides ``Statement'' and ``Annotation'') can cause a confusion of the coders and therefore compromise the validity of the coding procedure}. +There are very few research scenarios, in which it is necessary to complement the two existing types of statements with further ones or with an adjustment of type ``DNA statement''. +One of them would be, if you study two parallel yet different research questions, which employ the same dataset \emph{and} the same coders at the same time. +In this case, you could first rename the statement type ``DNA Statement'' by selecting it from the statement type menu, clicking the \code{Edit} button (see Figure~\ref{fig:stattype}), entering the new name (in this case: ``Statement for Research Project 1'') in the text field on top of the pop-up window (see Figure~\ref{fig:statdetail}) and pressing the \code{OK} button (see 5, Figure~\ref{fig:statdetail}). +Subsequently you would open a new pop-up window by clicking on the \code{Add} button in the statement type menu (left button in Figure~\ref{fig:stattype}). +Then name the new statement type (in this case: ``Statement for Research Project 2'') in the text field on top of the pop-up window and choose a color (different from the other type) by clicking on the colored button next to this text field. +Then you also need to specify the relevant variables synchronous to the procedure depicted in Section~\ref{subsec:adjusvarint}. +However, please evaluate carefully, if it is really neccesary for your second research interest that you specify a second statement type or if it would be possible to either conceptualize it as a variable of the existing statement type or study it sequentially or with a different set of coders (and therefore in a different \dna\ dataset). +\emph{More than two statement types (besides ``Statement'' and ``Annotation'') can cause a confusion of the coders and therefore compromise the validity of the coding procedure}. \section{Final Step: Approving your Workspace and Creating the DNA File} \label{sec:finalstep} -Finally, clicking on the \code{Summary} tab in the sidebar of the ``Create new database'' menu provides you with a summary of your choices in respect to the configuration of your coding process (see Figure~\ref{fig:summary}). After controlling each of the three information you can now create your database by clicking on the \code{Create database} button. If this button is disabled and you get the error ``No database selected'' (see Figure~\ref{fig:nodb}), you probably forgot to click the \textbf{Apply button} after specifying your database (see Section~\ref{subsec:createlocal}, step 3). After creating the database, the new database will open in the main DNA window (see Figure~\ref{fig:newdb}) and you can proceed towards loading up and organizing the raw data. +Finally, clicking on the \code{Summary} tab in the sidebar of the ``Create new database'' menu provides you with a summary of your choices in respect to the configuration of your coding process (see Figure~\ref{fig:summary}). +After controlling each of the three information you can now create your database by clicking on the \code{Create database} button. +If this button is disabled and you get the error ``No database selected'' (see Figure~\ref{fig:nodb}), you probably forgot to click the \code{Apply} button after specifying your database (see Section~\ref{subsec:createlocal}, step 3). +After creating the database, the new database will open in the main DNA window (see Figure~\ref{fig:newdb}) and you can proceed towards loading up and organizing the raw data. \begin{figure} \includegraphics[width=\linewidth]{04-14-summary} \caption{Summary of your about to be created \dna\ database} @@ -1146,12 +1221,19 @@ Finally, clicking on the \code{Summary} tab in the sidebar of the ``Create new d \chapter{Importing and Organizing your Raw Data} \label{chp:dna-import} -\chapterauthor{Felix Rolf Bossner} +\chapterauthor{Felix Rolf Bossner and Johannes Gruber} \FloatBarrier -This section describes how to upload and organize your research project's raw data---i.\,e., the text files (newspaper articles, press releases etc.) containing the uncoded statements---in DNA. First it will be layed out how you open an existing database---either locally or from a remote location. Then you will learn how to import new documenst into \dna---either by importing one document at a time or by selecting mutliple documents for import. Finally, we tell you how you can organise the documents in your database and how you can change your docuemtns' metadata. +This section describes how to upload and organize your research project's raw data---i.\,e., the text files (newspaper articles, press releases etc.) containing the uncoded statements---in DNA. +First it will be layed out how you open an existing database---either locally or from a remote location. +Then you will learn how to import new documenst into \dna---either by importing one document at a time or by selecting mutliple documents for import. +Finally, we tell you how you can organise the documents in your database and how you can change your docuemtns' metadata. \section{Opening an Existing DNA Database} -First of all, you have to choose, in which \dna\ Database you want to upload and process your data. To open a \dna database, simply follow the steps depicted in Figure 1: First, click on the index tab \code{File} and select the option \code{Open DNA database} (see Figure~\ref{fig:opendb}, step 1). As a result, a pop-up window will appear, which allows you to choose between opening a \code{Local .dna file} or a \code{remote database on a server}. If your database is stored on a remote server, you should choose the second option and repeat the procedure outlined in \fullref{subsec:usingremote}. If your dataset is stored in a folder on your local PC or device, you can proceed with the preset option and click on the button \code{Browse} (see Figure~\ref{fig:opendb}, step 2), which will open a further pop-up window, in which you can find your database by choosing its storage location from the \code{Save in} slide down menu (see step 3), selecting the respective database (see step 4) and clicking on the button \code{Open} both in the pop-up and the ``Open existing database...'' window (see steps 5 and 6). +First of all, you have to choose, in which \dna\ Database you want to upload and process your data. +To open a \dna database, simply follow the steps depicted in Figure 1: First, click on the index tab \code{File} and select the option \code{Open DNA database} (see Figure~\ref{fig:opendb}, step 1). +As a result, a pop-up window will appear, which allows you to choose between opening a \code{Local .dna file} or a \code{remote database on a server}. +If your database is stored on a remote server, you should choose the second option and repeat the procedure outlined in \fullref{subsec:usingremote}. + If your dataset is stored in a folder on your local PC or device, you can proceed with the preset option and click on the button \code{Browse} (see Figure~\ref{fig:opendb}, step 2), which will open a further pop-up window, in which you can find your database by choosing its storage location from the \code{Save in} slide down menu (see step 3), selecting the respective database (see step 4) and clicking on the button \code{Open} both in the pop-up and the ``Open existing database...'' window (see steps 5 and 6). \begin{figure} \includegraphics[width=\linewidth]{05-1-opendb} \caption{Opene \dna database} @@ -1163,18 +1245,26 @@ There are three %four different---partly semi-automatic---ways to upload your raw data and related descriptive information (title, date, author, source, section and type of document) into \dna: Importing single Documents manually via copy and paste, Importing multiple Documents semi-automatically from text files and importing Documents from other DNA databases. %and using \rdna\ to import data which is already available in R (see Section~\ref{subsec:importr})% -. All three +. +All three %four will be explained in detail in this section. \subsection{Importing Single Documents Manually via copy and paste} -The most basic way to import data to \dna\ requires you to manually copy and paste the content and the descriptive information for each of your documents into the text fields of a pop-up window, which you open by clicking on the index tab \code{Documents} and selecting the option \code{Add new document} (see Figure~\ref{fig:adddoc}). This window has eight text boxes, in which you can enter information from and about your source data (see Figure~\ref{fig:adddoc}): +The most basic way to import data to \dna\ requires you to manually copy and paste the content and the descriptive information for each of your documents into the text fields of a pop-up window, which you open by clicking on the index tab \code{Documents} and selecting the option \code{Add new document} (see Figure~\ref{fig:adddoc}). +This window has eight text boxes, in which you can enter information from and about your source data (see Figure~\ref{fig:adddoc}): \begin{itemize} - \item The field \code{title} is mandatory and may include any kind of information, for instance a unique ID if you plan to collect additional information about the articles in a separate database. Duplicate article titles are not allowed. - \item The field \code{date} is also mandatory and preset on the current time and day. You can change it by either clicking on the year, month, day or time and adjusting the respective value via the arrows on the right or by manually entering the date in the format \code{YYYY-MM-DD hh:mm:ss}. Please make sure you enter the date correctly because otherwise the algorithms for longitudinal data (see Section~\ref{sec:longi}) will not work properly. - \item The fields \code{author}, \code{source}, \code{section} and \code{type} are optional, but this additional information can help you to efficiently organize your data and ensure the reproducibilty, transparency and future usage of your research project. You can enter these information either manually or select an author, source, section or type you specified for a previously added document from the drop-down menu, which appears when you click on the downward arrow buttonon the left of the respective field. - \item To insert the content of your document, copy your article from a website or any other text source and paste it in the \textbf{text field (largest field at the bottom of the pop-up window)}. Single line breaks are automatically removed, while double line breaks (paragraph breaks) are preserved. Some escape sequences and special characters are automatically removed when text is inserted. + \item The field \code{title} is mandatory and may include any kind of information, for instance a unique ID if you plan to collect additional information about the articles in a separate database. +Duplicate article titles are not allowed. + \item The field \code{date} is also mandatory and preset on the current time and day. +You can change it by either clicking on the year, month, day or time and adjusting the respective value via the arrows on the right or by manually entering the date in the format \code{YYYY-MM-DD hh:mm:ss}. +Please make sure you enter the date correctly because otherwise the algorithms for longitudinal data (see Section~\ref{sec:longi}) will not work properly. + \item The fields \code{author}, \code{source}, \code{section} and \code{type} are optional, but this additional information can help you to efficiently organize your data and ensure the reproducibilty, transparency and future usage of your research project. +You can enter these information either manually or select an author, source, section or type you specified for a previously added document from the drop-down menu, which appears when you click on the downward arrow buttonon the left of the respective field. + \item To insert the content of your document, copy your article from a website or any other text source and paste it in the \emph{text field (largest field at the bottom of the pop-up window)}. +Single line breaks are automatically removed, while double line breaks (paragraph breaks) are preserved. +Some escape sequences and special characters are automatically removed when text is inserted. \item If you want to add further meta information to your document, which does not fit the preset categories, you can use the field \code{notes}. \end{itemize} Finally---after checking your specifications---you can import the document to \dna\ by clicking the \code{Add} button. @@ -1188,24 +1278,36 @@ Finally---after checking your specifications---you can import the document to \d \subsection{Importing Multiple Documents Semi-automatically from Text Files}\label{subsec:multiimport} -If you want to analyze a greater number of articles, it quickly becomes tedious to manually copy and paste each document and its meta data. This is why \dna\ also offers a semi-automatic way to upload multiple documents and their relevant meta data (author, date, source, type) at the same time. +If you want to analyze a greater number of articles, it quickly becomes tedious to manually copy and paste each document and its meta data. +This is why \dna\ also offers a semi-automatic way to upload multiple documents and their relevant meta data (author, date, source, type) at the same time. \subsubsection{Downloading and Preparing your Raw Data} -This way of importing raw data to \dna\ requires that you save all documents as \textbf{separate \code{.txt} files} (one file for each article) \textbf{in a common folder}. Please note, that you have to use the \code{.txt}format for saving your data, as \dna\ can not import \code{.doc} or \code{.pdf} files.\footnote{You can, however, save Word-documents as .txt files or use an online converter to transform PDFs into txt files. Note, that you need to make sure (both cases) that the .txt file is saved with UTF 8 encoding.} In case you use the newspaper database of LexisNexis---which is available through many university lbraries---for finding and retrieving your raw data, please make sure that you download all documents separately (by selecting the individual document before clicking the download button, \textit{see Figure~\ref{fig:nexis}, step 1-2}) and choose the document format \code{Text} (under \code{Format Options} in the Download pop-up menu, \textit{see Figure~\ref{fig:nexis}, step 3-4}) before downloading the data (see Figure~\ref{fig:nexis}, step 5).\footnote{If you use \rdna\ it will soon also be possible to import LexisNexis data into \dna\ via using \rdna\ and a new \R package called \href{https://github.com/JBGruber/LexisNexisTools}{LexisNexisTools} \citep{gruber2018lexis}.} +This way of importing raw data to \dna\ requires that you save all documents as \emph{separate \code{.txt} files} (one file for each article) \emph{in a common folder}. +Please note, that you have to use the \code{.txt}format for saving your data, as \dna\ can not import \code{.doc} or \code{.pdf} files.\footnote{You can, however, save Word-documents as .txt files or use an online converter to transform PDFs into txt files. +Note, that you need to make sure (both cases) that the .txt file is saved with UTF 8 encoding.} In case you use the newspaper database of LexisNexis---which is available through many university lbraries---for finding and retrieving your raw data, please make sure that you download all documents separately (by selecting the individual document before clicking the download button, see Figure~\ref{fig:nexis}, step 1-2) and choose the document format \code{Text} (under \code{Format Options} in the Download pop-up menu, (see Figure~\ref{fig:nexis}, step 3-4) before downloading the data (see Figure~\ref{fig:nexis}, step 5).\footnote{If you use \rdna\ it will soon also be possible to import LexisNexis data into \dna\ via using \rdna\ and a new \R package called \href{https://github.com/JBGruber/LexisNexisTools}{LexisNexisTools} \citep{gruber2018lexis}.} \begin{figure} \includegraphics[frame, width=\linewidth]{05-3-nexis} \caption{Downloading files from the LexisNexis newspaper archive} \label{fig:nexis} \end{figure} - If you want to use the preset regex configurations (\hyperref[subsubsec:adjregex]{in contrast to adjusting them}) for automatically detecting and uploading the meta data of your documents, you should use a \textbf{file name} in the format \code{DD.MM.YYYY - Author - Source - TYPE.txt} \textbf{with blanks before and after the minuses}, where \code{DD.MM.YYYY} is the date, on which the article was published. While \code{Author} and \code{Source} do not require a special format or length (e.\,g., you can use the first and/or last name of the author), the type of the document must always be indicated by capital letters. For example, the file name of the -article \url{http://spon.de/aeclD}, which is used as an example here, would have the format \code{31.03.2014 - Ralf Neukirch - SPON International - DIGITALRESOURCE.txt}. Please note, that plain text files are somtimes saved as \code{.TXT} instead of \code{.txt} files. While this is technically the same, it can cause problems while importing multiple text files. If this is the case, you have to either change the preset Regex configuration or correct the \code{.txt} suffix manually in the file name(s). Otherwise the automatic detection of your documents' meta data will not work. + If you want to use the preset regex configurations (\hyperref[subsubsec:adjregex]{in contrast to adjusting them}) for automatically detecting and uploading the meta data of your documents, you should use a \emph{file name} in the format \code{DD.MM.YYYY - Author - Source - TYPE.txt} \emph{with blanks before and after the minuses}, where \code{DD.MM.YYYY} is the date, on which the article was published. +While \code{Author} and \code{Source} do not require a special format or length (e.\,g., you can use the first and/or last name of the author), the type of the document must always be indicated by capital letters. +For example, the file name of the +article \url{http://spon.de/aeclD}, which is used as an example here, would have the format \code{31.03.2014 - Ralf Neukirch - SPON International - DIGITALRESOURCE.txt}. +Please note, that plain text files are somtimes saved as \code{.TXT} instead of \code{.txt} files. +While this is technically the same, it can cause problems while importing multiple text files. +If this is the case, you have to either change the preset Regex configuration or correct the \code{.txt} suffix manually in the file name(s). +Otherwise the automatic detection of your documents' meta data will not work. \subsubsection{Importing your Raw Data into DNA} If you prepared your data adequately, you can retrieve the documents and the relevant additional information in four simple steps (see Figure~\ref{fig:importtxt}): \begin{enumerate} - \item Click on the index tab \code{Documents} and select the option \code{Import text files} (see Figure~\ref{fig:importtxt}, step 1). As a result, a new window will open, in which you press the button \code{Select folder} (see step 2). This will open a further pop-up menu. Here, you have to select the \textbf{folder}, in which you saved the text files of your raw data, from the \textbf{\code{Look in} slide down menu} (see step 3) and click the button \code{Open} (see step 4). + \item Click on the index tab \code{Documents} and select the option \code{Import text files} (see Figure~\ref{fig:importtxt}, step 1). +As a result, a new window will open, in which you press the button \code{Select folder} (see step 2). +This will open a further pop-up menu. +Here, you have to select the \emph{folder}, in which you saved the text files of your raw data, from the \emph{\code{Look in} slide down menu} (see step 3) and click the button \code{Open} (see step 4). \begin{figure} \includegraphics[width=\linewidth]{05-4-importtxt} @@ -1213,8 +1315,12 @@ If you prepared your data adequately, you can retrieve the documents and the rel \label{fig:importtxt} \end{figure} - \item Now all documents, which are stored in the respective folder, should be listed in the main window of the \code{Import text files...} pop-up (see Figure~\ref{fig:txtfls}). If this isn't the case, please check if your documents are saved in the right file format (.txt). In order to check, whether \dna\ is able to automatically identify your documents' meta data, select one of the documents and click on the \code{Refresh} button (see Figure~\ref{fig:txtfls}). If you specified the file names correctly, you can now see the respective meta data of the selected document in the fields \code{Title}, \code{Author}, \code{Source}, \code{Type} and \code{Date} of the \code{Preview} Section at the bottom right of the ``Import text files'' window (see Figure~\ref{fig:txtfls}). - \item If you want to adjust or amend the meta data manually, just select the document, \textbf{uncheck} the box \code{Regex} of the field you want to edit and enter the new or additional information in the field on the left. Then click again on the \code{Refresh} button to check, whether your changes were accepted. + \item Now all documents, which are stored in the respective folder, should be listed in the main window of the \code{Import text files...} pop-up (see Figure~\ref{fig:txtfls}). +If this isn't the case, please check if your documents are saved in the right file format (.txt). +In order to check, whether \dna\ is able to automatically identify your documents' meta data, select one of the documents and click on the \code{Refresh} button (see Figure~\ref{fig:txtfls}). +If you specified the file names correctly, you can now see the respective meta data of the selected document in the fields \code{Title}, \code{Author}, \code{Source}, \code{Type} and \code{Date} of the \code{Preview} Section at the bottom right of the ``Import text files'' window (see Figure~\ref{fig:txtfls}). + \item If you want to adjust or amend the meta data manually, just select the document, \emph{uncheck} the box \code{Regex} of the field you want to edit and enter the new or additional information in the field on the left. +Then click again on the \code{Refresh} button to check, whether your changes were accepted. \item Finally, click on the button \code{Import files} to import all documents of the respective folder into your \dna\ database (you do not need to select each document for import). \begin{figure} \includegraphics[width=\linewidth]{05-5-txtfls} @@ -1225,23 +1331,37 @@ If you prepared your data adequately, you can retrieve the documents and the rel \end{enumerate} \subsubsection{Adjusting the Regex Configuration for automatic identification of meta data}\label{subsubsec:adjregex} -The previous steps assumed that you use the preset configuration of \dna\ to detect and upload the meta data (Title, Author, Source, Type, Date) of your documents automatically into your database. However, if you are interested in automatically importing additional information about your source data (in the fields \code{Section} or \code{Notes}) or if your file names depart from the naming system layed out here (but nevertheless contain all relevant information in a systematic order), \dna\ allows you to change, adjust or amend the pattern, through which the meta data about your documents is derived from the file names. The commands/rules, on which the ``translation'' of file names into meta data is based, are formulated in the -\href{https://en.wikipedia.org/wiki/Regular_expression}{Regular expessions (in short: Regex) syntax} and can be edited for each kind of information (Title, Author, Source, Section, Tyoe, Notes, Date) in the field \code{Pattern} on the bottom left of the ``Import text files...'' window (see Figure~\ref{fig:txtfls}). If you want to amend or adjust this settings it is recommended to use a Regex Cheatsheet (see e.\,g., +The previous steps assumed that you use the preset configuration of \dna\ to detect and upload the meta data (Title, Author, Source, Type, Date) of your documents automatically into your database. +However, if you are interested in automatically importing additional information about your source data (in the fields \code{Section} or \code{Notes}) or if your file names depart from the naming system layed out here (but nevertheless contain all relevant information in a systematic order), \dna\ allows you to change, adjust or amend the pattern, through which the meta data about your documents is derived from the file names. +The commands/rules, on which the ``translation'' of file names into meta data is based, are formulated in the +\href{https://en.wikipedia.org/wiki/Regular_expression}{Regular expessions (in short: Regex) syntax} and can be edited for each kind of information (Title, Author, Source, Section, Tyoe, Notes, Date) in the field \code{Pattern} on the bottom left of the ``Import text files...'' window (see Figure~\ref{fig:txtfls}). +If you want to amend or adjust this settings it is recommended to use a Regex Cheatsheet (see e.\,g., \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{cheatography.com} or -\href{http://www.txt2re.com/index-perl.php3?s=31.03.2014\%20-\%20Ralf\%20Neukirch\%20-\%20SPON\%20International\%20-\%20DIGITALRESOURCE.txt&-94&-102&80&77&75&81&-95&79&76&78&82&13&14&5&3}{this regex ``translator''}). As further support, \textit{Figure~\ref{fig:regex}} translates the preset regular expressions of the \dna\ \code{Import text files...} option. +\href{http://www.txt2re.com/index-perl.php3?s=31.03.2014\%20-\%20Ralf\%20Neukirch\%20-\%20SPON\%20International\%20-\%20DIGITALRESOURCE.txt&-94&-102&80&77&75&81&-95&79&76&78&82&13&14&5&3}{this regex ``translator''}). +As further support, Figure~\ref{fig:regex} translates the preset regular expressions of the \dna\ \code{Import text files...} option. \begin{figure} - \includegraphics[frame, width=\linewidth]{05-6-regex} + \includegraphics[width=\linewidth]{05-6-regex} \caption{Import text files} \label{fig:regex} \end{figure} \subsection{Importing Documents from Other \dna\ Databases}\label{subsec:merge} -You can also import documents from other \dna\ databases. This function is particularly relevant in two scenarios: First, if you not only want to use the \textbf{raw data, but also the coded statements} of an already finished research project, this function allows you to import both. Secondly, if there is \textbf{more than one person working on the same project at the same time} and you did not use multiple user roles (see Section~\ref{sec:userman}) to enable your coders to work on the same remote database. In the second scenario, you should use this function to prepare your datasets or merge the codings, as it is usually difficult to merge the files manually later on. In the latter scenario, the function helps you to avoid trouble with \textbf{duplicate statement IDs} and article names, as \dna\ will take care of e.\,g., duplicates automatically. - -Make sure, that you \textbf{know which version of DNA} (DNA 2.0 or older) was used to create and edit the database, from which you want to import data, \textbf{before} using the ``Import from DNA'' function. If you use this manual as a beginner's tutorial for working with \dna\ please download the file \code{sample.dna} from the \dna\ \url{https://github.com/leifeld/dna/releases}. This file contains a small selection of documents and statements from a larger project about congressional hearings on climate change, employed in the project described in \citet{fisher2013mapping, fisher2013where}. - -To import documents (and the included code statements), click on the index tab \code{Documents} and select the option \code{Import from DNA 2.0 file}, if \dna\ 2.0 was used to create and edit the database. As the internal structure of .dna files has significantly changed since version 1.31, databases created with an older version of \dna\ need to be impored using the seperate method \code{Import from DNA 1.31 file} (see Figure~\ref{fig:importdna}, step 1). As a result of either step, a further pop-up menu will open (see Figure~\ref{fig:importstat}). In this window, you have to select the \textbf{folder}, in which you saved the text files of your raw data, from the \code{Look in} slide down menu (see step 2) and \textbf{select the respective .dna file} (see step 3). Click the button \code{Open} (see step 4) to then open the menu depicted in \textit{Figure~\ref{fig:importstat}}. +You can also import documents from other \dna\ databases. +This function is particularly relevant in two scenarios: First, if you not only want to use the \emph{raw data, but also the coded statements} of an already finished research project, this function allows you to import both. +Secondly, if there is \emph{more than one person working on the same project at the same time} and you did not use multiple user roles (see Section~\ref{sec:userman}) to enable your coders to work on the same remote database. +In the second scenario, you should use this function to prepare your datasets or merge the codings, as it is usually difficult to merge the files manually later on. +In the latter scenario, the function helps you to avoid trouble with \emph{duplicate statement IDs} and article names, as \dna\ will take care of e.\,g., duplicates automatically. + +Make sure, that you \emph{know which version of DNA} (DNA 2.0 or older) was used to create and edit the database, from which you want to import data, \emph{before} using the ``Import from DNA'' function. +If you use this manual as a beginner's tutorial for working with \dna\ please download the file \code{sample.dna} from the \dna\ \url{https://github.com/leifeld/dna/releases}. +This file contains a small selection of documents and statements from a larger project about congressional hearings on climate change, employed in the project described in \citet{fisher2013mapping, fisher2013where}. + +To import documents (and the included code statements), click on the index tab \code{Documents} and select the option \code{Import from DNA 2.0 file}, if \dna\ 2.0 was used to create and edit the database. +As the internal structure of .dna files has significantly changed since version 1.31, databases created with an older version of \dna\ need to be impored using the seperate method \code{Import from DNA 1.31 file} (see Figure~\ref{fig:importdna}, step 1). +As a result of either step, a further pop-up menu will open (see Figure~\ref{fig:importstat}). +In this window, you have to select the folder, in which you saved the text files of your raw data, from the \code{Look in} slide down menu (see step 2) and \emph{select the respective \code{.dna} file} (see step 3). +Click the button \code{Open} (see step 4) to then open the menu depicted in Figure~\ref{fig:importstat}. \begin{figure} \includegraphics[width=\linewidth]{05-7-importdna} \caption{Import a \dna\ 2.0-database} @@ -1255,8 +1375,17 @@ To import documents (and the included code statements), click on the index tab \ \label{fig:importstat} \end{figure} -In this menu, you can select, which documents (and respective which coded statements) from the original \dna\ database you want to import in your database by either manually checking or unchecking the boxes on the left of the document title or by using the function ``Keyword filter''. This function is particularly helpful if you want to only import few documents with a specific common characteristic (author, topic) from a very large dataset. -Clicking on the button \code{Keyword filter...} (see left button in Figure~\ref{fig:importstat}) opens a new pop-up window, in which you can enter a specific search term. For example, if you downloaded and opened the \href{https://github.com/leifeld/dna/raw/master/manual/sample.dna}{\code{sample.dna}} file, you can select all congressional hearings of NGO representatives by \textbf{entering the keyword ``NGO''} in the text field and pressing the button \code{OK} in the ``Keyword filer'' pop-up window (see Figure~\ref{fig:importstat}). Now only the boxes of the three documents, which contain the hearings of NGO representatives Kateri Callahan, David Hamilton and Nayak Navin, should be checked, while the other boxes are unchecked. The ``Keyword filter'' function is based on the same regex syntax described in \fullref{subsubsec:adjregex}. This means, you can also use more specified regular expressions (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) to select certain articles. For example, if you enter a \code{\^N} in the ``Keyword filter'' \dna\ will select all articles starting with a capital N. If you want to undo your selections, you can also automatically select or unselect all articles by pressing the button \code{(Un)select all} in the middle of the ``Import statements'' window (see Figure~\ref{fig:importstat}). Pressing the right button \code{Import selected} in the same window imports all documents with a checked box (and the respective coded statements) in your \dna\ database (see Figure~\ref{fig:importstat}). If you use this manual as a beginner's tutorial for working with \dna, you should try importing all documents and the respective statements from the file \href{https://github.com/leifeld/dna/raw/master/manual/sample.dna}{\code{sample.dna}} into your database. +In this menu, you can select, which documents (and respective which coded statements) from the original \dna\ database you want to import in your database by either manually checking or unchecking the boxes on the left of the document title or by using the function ``Keyword filter''. +This function is particularly helpful if you want to only import few documents with a specific common characteristic (author, topic) from a very large dataset. +Clicking on the button \code{Keyword filter...} (see left button in Figure~\ref{fig:importstat}) opens a new pop-up window, in which you can enter a specific search term. +For example, if you downloaded and opened the \href{https://github.com/leifeld/dna/raw/master/manual/sample.dna}{\code{sample.dna}} file, you can select all congressional hearings of NGO representatives by \emph{entering the keyword ``NGO''} in the text field and pressing the button \code{OK} in the ``Keyword filer'' pop-up window (see Figure~\ref{fig:importstat}). +Now only the boxes of the three documents, which contain the hearings of NGO representatives Kateri Callahan, David Hamilton and Nayak Navin, should be checked, while the other boxes are unchecked. +The ``Keyword filter'' function is based on the same regex syntax described in \fullref{subsubsec:adjregex}. +This means, you can also use more specified regular expressions (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) to select certain articles. +For example, if you enter a \code{\^N} in the ``Keyword filter'' \dna\ will select all articles starting with a capital N. +If you want to undo your selections, you can also automatically select or unselect all articles by pressing the button \code{(Un)select all} in the middle of the ``Import statements'' window (see Figure~\ref{fig:importstat}). +Pressing the right button \code{Import selected} in the same window imports all documents with a checked box (and the respective coded statements) in your \dna\ database (see Figure~\ref{fig:importstat}). +If you use this manual as a beginner's tutorial for working with \dna, you should try importing all documents and the respective statements from the file \href{https://github.com/leifeld/dna/raw/master/manual/sample.dna}{\code{sample.dna}} into your database. %To DO %\subsection{Importing Documents using \R\}\label{subsec:importr} @@ -1266,25 +1395,39 @@ Clicking on the button \code{Keyword filter...} (see left button in Figure~\ref{ \section{Organizing Documents (Raw Data) } \subsection{Deleting and Navigating Through Documents} -All your imported documents are listed in the upper middle table of the \dna\ main window. If you click on an article, its corresponding text (i. e. the speech) will be displayed in the text area below the document table. By clicking on, for example, the entry \code{109-1: Callahan, Kateri-NGO-Y} you open the speech of Kateri Callahan, a representative of the Alliance to Save Energy. You can adjust the size of the document table (by clicking on the bar above the text area and moving it vertically with your cursor) or its colums (by clicking on the edge of the column and moving it horizontally with your cursor). You can also customize the meta information, which are displayed in the document table: Just \textbf{right click on any document} and use the appearing \textbf{context menu} to (un-)check the boxes of the information you (don't) want to be displayed (see Figure~\ref{fig:batchrecode}, step 1). A structured (and customised) overview of your raw data is essential for detecting missing information and thus efficiently controlling, organizing and coding your data. For example, if you display the meta information ``Type'' (by checking the respective box in the context menu), you can see that the type of all documents from the \code{sample.dna} file is not listed. +All your imported documents are listed in the upper middle table of the \dna\ main window. +If you click on an article, its corresponding text (i.\,e., the speech) will be displayed in the text area below the document table. +By clicking on, for example, the entry \code{109-1: Callahan, Kateri-NGO-Y} you open the speech of Kateri Callahan, a representative of the Alliance to Save Energy. +You can adjust the size of the document table (by clicking on the bar above the text area and moving it vertically with your cursor) or its colums (by clicking on the edge of the column and moving it horizontally with your cursor). +You can also customize the meta information, which are displayed in the document table: Just right click on any document and use the appearing context menu to (un-)check the boxes of the information you (don't) want to be displayed (see Figure~\ref{fig:batchrecode}, step 1). +A structured (and customised) overview of your raw data is essential for detecting missing information and thus efficiently controlling, organizing and coding your data. +For example, if you display the meta information ``Type'' (by checking the respective box in the context menu), you can see that the type of all documents from the \code{sample.dna} file is not listed. \begin{figure} \includegraphics[width=\linewidth]{05-9-batchrecode} \caption{Import Statements menu} \label{fig:batchrecode} \end{figure} -The same context menu can be used to delete documents from your database by \textbf{selecting the documents} you want to delete (pressing and holding the \code{Ctrl} key for selecting multiple documents), opening the context menu with a \textbf{right click} and choosing the option \code{Delete selected documents}. +The same context menu can be used to delete documents from your database by \emph{selecting the documents} you want to delete (pressing and holding the \code{Ctrl} key for selecting multiple documents), opening the context menu with a \emph{right click} and choosing the option \code{Delete selected documents}. \subsection{Editing the Documents' Metadata (Author, Time etc...)} -DNA allows you to edit, delete or complement the descriptive information related to your raw data (title, date, author, source, section and type of document). Similiar to the procedures outlined in Section~\ref{sec:importdoc} there is a manual as well as a semi-automatic way to adjust the meta data of your documents. +DNA allows you to edit, delete or complement the descriptive information related to your raw data (title, date, author, source, section and type of document). +Similiar to the procedures outlined in Section~\ref{sec:importdoc} there is a manual as well as a semi-automatic way to adjust the meta data of your documents. \subsubsection{Editing the documents' meta data manually} -The most basic way to edit your documents' meta data is to \textbf{select the document}, of which you want to edit the information (by left-clicking on it) and adjusting the values in the \code{Document properties} submenu on the middle left of the \dna\ main window (see Figure~\ref{fig:batchrecode}, step 2) by either manually typing in the relevant information or by selecting an already specified author, a source, a section or a type from the \textbf{drop-down menu} on the right of the respective meta field. For example, in \textit{Figure~\ref{fig:batchrecode} (step 2}) Kateri Callahans speech was selected, and the value ``NGO'' (for Non-Governmental Organisation) was manually specified as ``Type of document'' by entering it in the field \code{Type} of the ``Document properties'' submenu. Do not forget to \textbf{press the button \code{Save}} in the submenu (see Figure~\ref{fig:batchrecode}, step 2) to confirm your edits. +The most basic way to edit your documents' metadata is to \emph{select the document}, of which you want to edit the information (by left-clicking on it) and adjusting the values in the \code{Document properties} submenu on the middle left of the \dna\ main window (see Figure~\ref{fig:batchrecode}, step 2) by either manually typing in the relevant information or by selecting an already specified author, a source, a section or a type from the drop-down menu on the right of the respective meta field. +For example, in Figure~\ref{fig:batchrecode} (step 2) Kateri Callahans speech was selected, and the value ``NGO'' (for Non-Governmental Organisation) was manually specified as ``Type of document'' by entering it in the field \code{Type} of the ``Document properties'' submenu. +Do not forget to press the button \code{Save} in the submenu (see Figure~\ref{fig:batchrecode}, step 2) to confirm your edits. -Please note, that you can manually only edit the meta data of \textbf{one document at one time}. If you try to select multiple documents for editing, the ``Document properties'' submenu will disappear, returning ``(No document or permission)''. +Please note, that you can manually only edit the meta data of \emph{one document at one time}. +If you try to select multiple documents for editing, the ``Document properties'' submenu will disappear, returning ``(No document or permission)''. \subsubsection{Editing the documents' meta data semi-automatically} -However if you want to adjust the meta data of a greater number of articles, it quickly becomes tedious to manually edit information about each document. This is why \dna\ also offers a semi-automatic way to edit, delete or complement the descriptive information related to your documents. In order to edit your documents' meta data semi-automatically, click on the index tab \code{Documents} and select the option \code{Batch-recode meta-data} (see Figure~\ref{fig:batchrecode}, step 3). As a result, a pop-up window similiar to \textit{Figure~\ref{fig:recodewin}} will open. In the upper half of this pop-up window you find nine fields, which can be configured in order to adjust the meta data for \textbf{multiple documents at once}: +However if you want to adjust the meta data of a greater number of articles, it quickly becomes tedious to manually edit information about each document. +This is why \dna\ also offers a semi-automatic way to edit, delete or complement the descriptive information related to your documents. +In order to edit your documents' meta data semi-automatically, click on the index tab \code{Documents} and select the option \code{Batch-recode meta-data} (see Figure~\ref{fig:batchrecode}, step 3). +As a result, a pop-up window similiar to Figure~\ref{fig:recodewin} will open. +In the upper half of this pop-up window you find nine fields, which can be configured in order to adjust the meta data for \emph{multiple documents at once}: \begin{figure} \centering \includegraphics[frame, width=0.75\linewidth]{05-10-recodewin} @@ -1294,34 +1437,63 @@ However if you want to adjust the meta data of a greater number of articles, it \begin{itemize} \item The field \code{Target field:} specifies, which kind of meta information (i.\,e., title, author, source, section, type, notes) should be adjusted by choosing the respective meta data category from the slide-down menu (which you open by clicking the arrow on the right of the target field). - \item The field \code{Source field:} specifies, where the data you want to use for adjusting the target field is stored. For example, if you simply want to delete or correct (e.\,g., misspelt) title-, author-, source-, section-, type- or notes-metadata, you usually choose the same field as source field as you have chosen as target field, since you want to adjust the data already stored in this field. However, if you want to add new data to a (maybe empty or incomplete) target field, you have to choose the part of the meta information as source field, which contains the information, from which you want to derive the new data. As the document title should contain all relevant meta information, \code{Title} is usually used as source field for the latter case. - \item The field \code{Matching on target regex} allows you to automatically delimit the documents which you want to adjust, based on the information stored in the document's target field. Similiar to all regex implementations in \dna\ you can either use search terms or regular expressions to filter the documents. If you, for instance, misspelt the author ``Ralf Neukirch'' sometimes as ``Ralf Neu\textbf{n}kirch'', you can correct all your misspellings by simply selecting ``Author'' as \code{Target field}, entering ``Ralf Neu\textbf{n}kirch'' in the field \code{Matching on target regex:} and the correct version (``Ralf Neukirch'') in the field \code{New target field}. As \code{Matching on target regex} automatically deselects all non-matching cases (here: All documents, who do not have ``Ralf Neunkirch'' specified as their author), the meta information (here: ``Author'') remains the same for all other documents. - \item The field \code{Matching on source regex} similarly allows you to automatically filter the documents of which you want to alter the meta data, based on the information stored in the document's source field. For example, if you realise that Ralf Neukirch does not write for ``SPON International'' (as you erroneously specified), but for ``THE GUARDIAN'', you can simply correct all your misspecifications by first selecting \code{Source} as the \code{Target field} and \code{Author} as the \code{Source field}, secondly entering ``Ralf Neukirch'' in the field \code{Matching on source regex} and then specifying ``THE GUARDIAN'' as \code{New target field}. - \item The field \code{\%target regular expression} allows you to specify/match a part of the target field, which you want to use as new information in the same field. For example, if the field \code{Author} somehow contains the full document titles you can reduce the information in the field \code{Author} to just the name of the respective author by entering the regular expression \code{(?<=.+?---).+?(?= -)} (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) in the field \code{\%target regular expression} and entering \code{\%target} in the field \code{New target field}. \textbf{Please note, that if you do not use this function, you should not change the preset value \code{.+} in this field}---because if you do, your recoding might not obtain the expected results. - \item The field \code{\%target replacement} defines a new value for the information in the target field---similarly to the fields \code{New target field} and \code{\%source replacement}. If you use \code{\%target} as \code{New target field}, you have to specify the new, additional, corrected or reduced information in this field. - \item The field \code{\%source regular expression} allows you to specify/match a part of the source field, which you want to use as new information in the target field. For example, if your source field is \code{Title} and the titles of your documents have the recommended format (i.\,e., \code{DD.MM.YYYY - Author - Source - TYPE.txt} with blanks before and after the minuses; see Section~\ref{subsec:multiimport}) you can automatically specify the meta information for the field \code{Author} by (1.)~choosing \code{Author} as the \code{Target field} and \code{Title} as the \code{Source field}, (2.)~entering the regular expression \code{(?<=.+?---).+?(?= -)} (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) in the field \code{\%source regular expression} and (3.)~entering \code{\%source} in the field \code{New target field}. \textbf{Please note, that if you do not use this function, you should not change the preset value \code{.+} in this field}---because if you do, your recoding might not obtain the expected results. - \item The field \code{\%source replacement}---similarly to the fields \code{New target field} and \code{\%target replacement}---defines a new value for the information in the target field. If you use \code{\%source} as \code{New target field}, you have to specify the new, additional, corrected or reduced information in this field. - \item The field \code{New target field} defines the new, corrected, reduced or additional data, which is entered in your target field (see examples above). Please note, that this field has to be set on \code{\%source} (preset value) if you use the functions \code{\%source regular expression} or \code{\%source replacement} and has to be set on \code{\%target} if you use the functions \code{\%target regular expression} or \code{\%target replacement}. Otherwise, the respective functions will not work. + \item The field \code{Source field:} specifies, where the data you want to use for adjusting the target field is stored. +For example, if you simply want to delete or correct (e.\,g., misspelt) title-, author-, source-, section-, type- or notes-metadata, you usually choose the same field as source field as you have chosen as target field, since you want to adjust the data already stored in this field. +However, if you want to add new data to a (maybe empty or incomplete) target field, you have to choose the part of the meta information as source field, which contains the information, from which you want to derive the new data. +As the document title should contain all relevant meta information, \code{Title} is usually used as source field for the latter case. + \item The field \code{Matching on target regex} allows you to automatically delimit the documents which you want to adjust, based on the information stored in the document's target field. +Similiar to all regex implementations in \dna\ you can either use search terms or regular expressions to filter the documents. +If you, for instance, misspelt the author ``Ralf Neukirch'' sometimes as ``Ralf Neu\emph{n}kirch'', you can correct all your misspellings by simply selecting ``Author'' as \code{Target field}, entering ``Ralf Neu\emph{n}kirch'' in the field \code{Matching on target regex:} and the correct version (``Ralf Neukirch'') in the field \code{New target field}. +As \code{Matching on target regex} automatically deselects all non-matching cases (here: All documents, who do not have ``Ralf Neunkirch'' specified as their author), the meta information (here: ``Author'') remains the same for all other documents. + \item The field \code{Matching on source regex} similarly allows you to automatically filter the documents of which you want to alter the meta data, based on the information stored in the document's source field. +For example, if you realise that Ralf Neukirch does not write for ``SPON International'' (as you erroneously specified), but for ``THE GUARDIAN'', you can simply correct all your misspecifications by first selecting \code{Source} as the \code{Target field} and \code{Author} as the \code{Source field}, secondly entering ``Ralf Neukirch'' in the field \code{Matching on source regex} and then specifying ``THE GUARDIAN'' as \code{New target field}. + \item The field \code{\%target regular expression} allows you to specify/match a part of the target field, which you want to use as new information in the same field. +For example, if the field \code{Author} somehow contains the full document titles you can reduce the information in the field \code{Author} to just the name of the respective author by entering the regular expression \code{(?<=.+?---).+?(?= -)} (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) in the field \code{\%target regular expression} and entering \code{\%target} in the field \code{New target field}. +\emph{Please note, that if you do not use this function, you should not change the preset value \code{.+} in this field}---because if you do, your recoding might not obtain the expected results. + \item The field \code{\%target replacement} defines a new value for the information in the target field---similarly to the fields \code{New target field} and \code{\%source replacement}. +If you use \code{\%target} as \code{New target field}, you have to specify the new, additional, corrected or reduced information in this field. + \item The field \code{\%source regular expression} allows you to specify/match a part of the source field, which you want to use as new information in the target field. +For example, if your source field is \code{Title} and the titles of your documents have the recommended format (i.\,e., \code{DD.MM.YYYY - Author - Source - TYPE.txt} with blanks before and after the minuses; see Section~\ref{subsec:multiimport}) you can automatically specify the meta information for the field \code{Author} by (1.)~choosing \code{Author} as the \code{Target field} and \code{Title} as the \code{Source field}, (2.)~entering the regular expression \code{(?<=.+?---).+?(?= -)} (see Figure~\ref{fig:regex} or \href{https://www.cheatography.com/davechild/cheat-sheets/regular-expressions/}{regex cheatsheet}) in the field \code{\%source regular expression} and (3.)~entering \code{\%source} in the field \code{New target field}. +\emph{Please note, that if you do not use this function, you should not change the preset value \code{.+} in this field}---because if you do, your recoding might not obtain the expected results. + \item The field \code{\%source replacement}---similarly to the fields \code{New target field} and \code{\%target replacement}---defines a new value for the information in the target field. +If you use \code{\%source} as \code{New target field}, you have to specify the new, additional, corrected or reduced information in this field. + \item The field \code{New target field} defines the new, corrected, reduced or additional data, which is entered in your target field (see examples above). +Please note, that this field has to be set on \code{\%source} (preset value) if you use the functions \code{\%source regular expression} or \code{\%source replacement} and has to be set on \code{\%target} if you use the functions \code{\%target regular expression} or \code{\%target replacement}. +Otherwise, the respective functions will not work. \end{itemize} The lower half of the ``Recode document meta-data'' pop-up window (see Figure~\ref{fig:recodewin}) displays a table with four columns and a row for each of your documents, which help you to preview, control and trace back your changes to the meta data: \begin{itemize} - \item The column \code{ID} contains the individual ID of each of your documents. This column can be particularly helpful if you specify a recoding procedures for a certain set of documents. If you know the ID of a few exemplary documents from this set, you can quickly trace back and understand the consequences of your recoding specifications by scrolling down to the respective IDs and taking a look at the other columns of these documents. - \item The column \code{Source field} displays the field, from which you get the meta data for recoding the target field. It is particularly helpful to understand the sequence of information in the source field, if you want to specify a \code{\%source regular expression} or use \code{Matching on source regex} (for example, if only some source fields contain the relevant information). - \item The column \code{Old target field} shows the meta data in the target fields prior to your adjustments. It is particularly helpful if you want to use \code{\%target regular expression} or use \code{Matching on target regex} (for example, if you only want to change the value of a certain set of target fields). - \item The column \code{New target field} displays the consequences of your adjustment. It is particular helpful to check if your recoding will be successful or if some recoding outcomes are actually undesired (for example, if the target field already contained the relevant information, but is recoded nevertheless). + \item The column \code{ID} contains the individual ID of each of your documents. +This column can be particularly helpful if you specify a recoding procedures for a certain set of documents. +If you know the ID of a few exemplary documents from this set, you can quickly trace back and understand the consequences of your recoding specifications by scrolling down to the respective IDs and taking a look at the other columns of these documents. + \item The column \code{Source field} displays the field, from which you get the meta data for recoding the target field. +It is particularly helpful to understand the sequence of information in the source field, if you want to specify a \code{\%source regular expression} or use \code{Matching on source regex} (for example, if only some source fields contain the relevant information). + \item The column \code{Old target field} shows the meta data in the target fields prior to your adjustments. +It is particularly helpful if you want to use \code{\%target regular expression} or use \code{Matching on target regex} (for example, if you only want to change the value of a certain set of target fields). + \item The column \code{New target field} displays the consequences of your adjustment. +It is particular helpful to check if your recoding will be successful or if some recoding outcomes are actually undesired (for example, if the target field already contained the relevant information, but is recoded nevertheless). \end{itemize} -Your recodings are only applied, if you press the button \code{Recode} (on the lower right of the \code{Recode document meta data} window, see Figure~\ref{fig:recodewin}). \textbf{Once this is applied, it cannot be undone!} So please control the consequences of your recodings by using the table at the lower half of the window. However, before pressing the \code{Recode} button, you \textit{can} revert all adjustments by pressing the button \code{Revert changes} and therefore are able to experiment with the meta data (regex) specifications. +Your recodings are only applied, if you press the button \code{Recode} (on the lower right of the \code{Recode document meta data} window, see Figure~\ref{fig:recodewin}). +\emph{Once this is applied, it cannot be undone!} So please control the consequences of your recodings by using the table at the lower half of the window. +However, before pressing the \code{Recode} button, you \emph{can} revert all adjustments by pressing the button \code{Revert changes} and therefore are able to experiment with the meta data (regex) specifications. -As noted previously, all documents from the file \code{sample.dna} do not specify any meta data concerning the type of the respective document. Both \textbf{Figure~\ref{fig:recodewin}} and \textbf{Figure~\ref{fig:recoderegex}} illustrate an exemplary semi-automatic procedure for complementing this information based on the information stored in the document title (here: The organisation, to which the respective speaker belongs to). Thus in both examples, \code{Type} is selected as \code{Target field}, while \code{Title} is selected as \code{Source field}. +As noted previously, all documents from the file \code{sample.dna} do not specify any meta data concerning the type of the respective document. +Both Figure~\ref{fig:recodewin} and Figure~\ref{fig:recoderegex} illustrate an exemplary semi-automatic procedure for complementing this information based on the information stored in the document title (here: The organisation, to which the respective speaker belongs to). +Thus in both examples, \code{Type} is selected as \code{Target field}, while \code{Title} is selected as \code{Source field}. -The example in \textbf{Figure~\ref{fig:recodewin}} uses \textbf{manual search terms} to specify the meta information for the document type. By entering ``NGO'' in the field \code{Matching on source regex} the adjustments are limited to the documents, which contain ``NGO'' in the document title. By entering ``NGO'' in the field \code{New target field}, the new value for \code{Type} is specified for the selected documents. As you can see in the table on the lower half of the \code{Recode meta-data} window, this very simple procedure is insofar successful, as only the target fields of documents containing hearings of NGO-representatives are changed and the target fields of all other documents (including those with already correct \code{Type} information) remain unchanged. However, this procedure would have to be repeated for each kind of organisation from the sample (NGO, GOV, BUS). +The example in Figure~\ref{fig:recodewin} uses manual search terms to specify the meta information for the document type. +By entering ``NGO'' in the field \code{Matching on source regex} the adjustments are limited to the documents, which contain ``NGO'' in the document title. +By entering ``NGO'' in the field \code{New target field}, the new value for \code{Type} is specified for the selected documents. +As you can see in the table on the lower half of the \code{Recode meta-data} window, this very simple procedure is insofar successful, as only the target fields of documents containing hearings of NGO-representatives are changed and the target fields of all other documents (including those with already correct \code{Type} information) remain unchanged. +However, this procedure would have to be repeated for each kind of organisation from the sample (NGO, GOV, BUS). -The more elegant way of semi-automatically specifying meta information is depicted in \textbf{Figure~\ref{fig:recoderegex}}, which uses the \textbf{Regex-syntax}. +The more elegant way of semi-automatically specifying meta information is depicted in Figure~\ref{fig:recoderegex}, which uses the \emph{Regex-syntax}. Here, by entering \texttt{\^?} in the field \code{Matching on target regex}, only those documents are selected for amendment, which do not already contain any information about the document type (therefore excluding those documents with already correct \code{Type} information). -By specifying \code{(?<=.+?-)[A-Z]+} as \code{\%source regular expression} (and accordingly \code{\%source} as \code{New target field}), \dna\ is instructed to filter any string of upper-case characters before a minus in the document title and set it as a new value for \code{Type}. Thus you can recode the document type for all documents at once, ensuring that already specified values are not overwritten---as evident from the table in the lower half of the window. +By specifying \code{(?<=.+?-)[A-Z]+} as \code{\%source regular expression} (and accordingly \code{\%source} as \code{New target field}), \dna\ is instructed to filter any string of upper-case characters before a minus in the document title and set it as a new value for \code{Type}. +Thus you can recode the document type for all documents at once, ensuring that already specified values are not overwritten---as evident from the table in the lower half of the window. \begin{figure} \includegraphics[width=\linewidth]{05-11-recoderegex} \caption{Meta information recode window (regex explained)} @@ -1335,11 +1507,21 @@ By specifying \code{(?<=.+?-)[A-Z]+} as \code{\%source regular expression} (and \FloatBarrier \chapter{Coding the Data}\label{chp:dna-coding} \chapterauthor{Johannes Gruber} -Now that you know how to create a database and organise the documents in it, it's time to start with the actual coding. This section describes how to create, edit and navigate through statements as well as how to employ the regex highlighter and search function to make coding of statements easier and faster. If you want to recreate the steps outlined in this section for practice, you should download the file \code{sample.dna} from the \dna\ \url{https://github.com/leifeld/dna/releases} and open it with the newest version of \dna\ from the same page---if you haven't already done that. +Now that you know how to create a database and organise the documents in it, it's time to start with the actual coding. +This section describes how to create, edit and navigate through statements as well as how to employ the regex highlighter and search function to make coding of statements easier and faster. +If you want to recreate the steps outlined in this section for practice, you should download the file \code{sample.dna} from the \dna\ \url{https://github.com/leifeld/dna/releases} and open it with the newest version of \dna\ from the same page---if you haven't already done that. \section{Creating a \dna\ Statement}\label{sec:createstat} \FloatBarrier -For the sake of this tutorial, we can create a new coder. You could also select one of the existing coders from the drop-down menu to create statements but it's just nicer if our new statement is associated with our names. Simply click on the plus sign in the coder menu in the upper left corner of the main window (see Figure~\ref{fig:newuser}, step 1). In the new menu that opens, enter your name and just leave all permissions selected for now (see Figure~\ref{fig:newuser}, step 2). Then you should choose a personal colour. Either you select a predefined one from the swatches tab or you define your own colour using one of the menus in the other tabs (see Figure~\ref{fig:newuser}, step 3). Later on, the statements you have created will be highlighted in this colour. After accepting the edit, you can select yourself from the drop-down coder menu. This should always be the first step before you or one of your coders start to work on the database. +For the sake of this tutorial, we can create a new coder. +You could also select one of the existing coders from the drop-down menu to create statements but it's just nicer if our new statement is associated with our names. +Simply click on the plus sign in the coder menu in the upper left corner of the main window (see Figure~\ref{fig:newuser}, step 1). +In the new menu that opens, enter your name and just leave all permissions selected for now (see Figure~\ref{fig:newuser}, step 2). +Then you should choose a personal colour. +Either you select a predefined one from the swatches tab or you define your own colour using one of the menus in the other tabs (see Figure~\ref{fig:newuser}, step 3). +Later on, the statements you have created will be highlighted in this colour. +After accepting the edit, you can select yourself from the drop-down coder menu. +This should always be the first step before you or one of your coders start to work on the database. \begin{figure} \includegraphics[frame, width=\linewidth]{06-01-newuser} \caption{Create your own personal user for this exercise} @@ -1351,23 +1533,47 @@ For the sake of this tutorial, we can create a new coder. You could also select \label{fig:newstatement} \end{figure} -To code a new \dna\ Statement, simply select a chunk of text by pressing and holding your left mouse button while sliding over it. When all the text you want to include in the statement is selected, push the right mouse button and select \code{Format as DNA Statement} from the appearing drop-down menu (see Figure~\ref{fig:newuser}). In the new menu that opens, you need to provide the details for the statement. Every \dna\ Statement consists of four pieces of information which you should ideally all provide (Figure~\ref{fig:statdetails}): +To code a new \dna\ Statement, simply select a chunk of text by pressing and holding your left mouse button while sliding over it. +When all the text you want to include in the statement is selected, push the right mouse button and select \code{Format as DNA Statement} from the appearing drop-down menu (see Figure~\ref{fig:newuser}). +In the new menu that opens, you need to provide the details for the statement. +Every \dna\ Statement consists of four pieces of information which you should ideally all provide (Figure~\ref{fig:statdetails}): -\begin{itemize} - \item \textbf{Person.} The person or actor who speaks or makes the statement. In discourse network analysis it is most often assumed that the organisation, not the person, are the important actors in a policy process. So if you have decided from the start of a project that this is the case, you could leave the person filed empty. However, it might nevertheless be interesting in a later step if there are differences between persons from the same organisation, so it is advised that you complete all fields. - \item \textbf{Organization.} The organisation the person who makes a statement is affiliated with. - \item \textbf{Concept.} The concept to which the statement refers. Concepts are usually abstract representations of the topics which are discussed. In advocacy coalition research, for example, concepts are claims for +\begin{description} + \item[Person] The person or actor who speaks or makes the statement. +In discourse network analysis it is most often assumed that the organisation, not the person, are the important actors in a policy process. +So if you have decided from the start of a project that this is the case, you could leave the person filed empty. +However, it might nevertheless be interesting in a later step if there are differences between persons from the same organisation, so it is advised that you complete all fields. + \item[Organization] The organisation the person who makes a statement is affiliated with. + \item[Concept] The concept to which the statement refers. +Concepts are usually abstract representations of the topics which are discussed. +In advocacy coalition research, for example, concepts are claims for policy instruments such as ``CO\textsubscript{2} legislation will not hurt the economy''. - \item \textbf{Agreement.} A dummy variable (i.\,e., a variable with only two possible outcomes) indicating whether the actor agrees with the category or not. Often this is a question of sentiment: if the speaker talks about the concept in a positive way we assume s/he agrees with it. And likewise that s/he disagrees when making a statement in a negative tone. As opposed to the other three fields, it is not possible to \textit{not} provide this information. If you do not tick the box \code{agreement} you indicate disagreement with the selected concept. -\end{itemize} - -There are two ways to provide the information: you can either click inside one of the boxes to write in a new category or you can choose a category from the drop-down menu (see Figure~\ref{fig:statdetails}). In the first case, \dna\ will try to auto-complete your code by using all existing categories, so you can leave a field incomplete and thereby choose an existing category. In the latter case, the drop-down menu shows all previously coded information, so that it is not necessary to reenter previously coded categories. This is not only convenient but also serves a reliability purpose: multiple similar but not identical categories, created by misspelling or incorrect abbreviation, would lead to spurious results which could jeopardize analysis later on. - -As you can see in Figure~\ref{fig:statdetails}, each statement also has a unique identification number. The ID can't be changed by the user, but it can be used as a primary key if you want to record additional information about your statements in a separate database---e.\,g., to automatically merge the information again once you move to analysis in \R\ or other programs. - -There are also two more symbols in the upper right corner of the Statement window: a plus sign, which creates a copy of the current statement. This can be helpful if the same text passage can be coded as multiple statements, for example, when it mentions multiple persons or organisations which refer to the same concept. And a trash bin symbol, which completly removes your \dna\ Statement, but leaves the document intact (see Figure~\ref{fig:statdetails}). + \item[Agreement] A dummy variable (i.\,e., a variable with only two possible outcomes) indicating whether the actor agrees with the category or not. +Often this is a question of sentiment: if the speaker talks about the concept in a positive way we assume s/he agrees with it. +And likewise that s/he disagrees when making a statement in a negative tone. +As opposed to the other three fields, it is not possible to \emph{not} provide this information. +If you do not tick the box \code{agreement} you indicate disagreement with the selected concept. +\end{description} -After you are done providing the detail information, you can simply click anywhere outside the menu to return to the main window. The moment you leave the \dna\ Statement window, all your edits are saved in your database---so there is no need to apply the changes or save your progress periodically (see Figure~\ref{fig:statdetails}). If you click outside the window by accident, you can return to edit the statement by simply clicking on it again (more in the next section). After you return to the main page, the statement is now highlighted either in yellow or in the personal colour of the coder you selected (see Figure~\ref{fig:stathl}). All \dna\ Statements have the colour which was selected when the \dna\ database was created. The only way to change the highlight colour would be to create a new database. However, by opening the \code{Settings} and selecting \code{Color statements by coder} the highlight colour changes to the colour of the coder who created each statement. +There are two ways to provide the information: you can either click inside one of the boxes to write in a new category or you can choose a category from the drop-down menu (see Figure~\ref{fig:statdetails}). +In the first case, \dna\ will try to auto-complete your code by using all existing categories, so you can leave a field incomplete and thereby choose an existing category. +In the latter case, the drop-down menu shows all previously coded information, so that it is not necessary to reenter previously coded categories. +This is not only convenient but also serves a reliability purpose: multiple similar but not identical categories, created by misspelling or incorrect abbreviation, would lead to spurious results which could jeopardize analysis later on. + +As you can see in Figure~\ref{fig:statdetails}, each statement also has a unique identification number. +The ID can't be changed by the user, but it can be used as a primary key if you want to record additional information about your statements in a separate database---e.\,g., to automatically merge the information again once you move to analysis in \R\ or other programs. + +There are also two more symbols in the upper right corner of the Statement window: a plus sign, which creates a copy of the current statement. +This can be helpful if the same text passage can be coded as multiple statements, for example, when it mentions multiple persons or organisations which refer to the same concept. +And a trash bin symbol, which completly removes your \dna\ Statement, but leaves the document intact (see Figure~\ref{fig:statdetails}). + +After you are done providing the detail information, you can simply click anywhere outside the menu to return to the main window. +The moment you leave the \dna\ Statement window, all your edits are saved in your database---so there is no need to apply the changes or save your progress periodically (see Figure~\ref{fig:statdetails}). +If you click outside the window by accident, you can return to edit the statement by simply clicking on it again (more in the next section). +After you return to the main page, the statement is now highlighted either in yellow or in the personal colour of the coder you selected (see Figure~\ref{fig:stathl}). +All \dna\ Statements have the colour which was selected when the \dna\ database was created. +The only way to change the highlight colour would be to create a new database. +However, by opening the \code{Settings} and selecting \code{Color statements by coder} the highlight colour changes to the colour of the coder who created each statement. \begin{figure} \includegraphics[frame, width=\linewidth]{06-03-statdetails} \caption{Create new \dna\ Statement} @@ -1379,24 +1585,46 @@ After you are done providing the detail information, you can simply click anywhe \label{fig:stathl} \end{figure} -Besides \dna\ Statements, you can also create annotations. In the sample database, annotations are highlighted in grey. You can use this feature, for example, if you are not quite sure if a text passage is a statement. Then you or another coder could review all annotations later on and decide if it should be coded as a statement or not. In projects with multiple coders who work on a remote database, the feature can also serve as a mean of communication between coders, for example, to provide instructions for a specific document or to make each other aware of a certain sentence or paragraph which might not be a statement but nevertheless important in other ways. Basically, annotations in \dna\ work in the same way as in MS Word, Goocle Docs and other applications. +Besides \dna\ Statements, you can also create annotations. +In the sample database, annotations are highlighted in grey. +You can use this feature, for example, if you are not quite sure if a text passage is a statement. +Then you or another coder could review all annotations later on and decide if it should be coded as a statement or not. +In projects with multiple coders who work on a remote database, the feature can also serve as a mean of communication between coders, for example, to provide instructions for a specific document or to make each other aware of a certain sentence or paragraph which might not be a statement but nevertheless important in other ways. +Basically, annotations in \dna\ work in the same way as in MS Word, Goocle Docs and other applications. \FloatBarrier \section{Navigating Through Statements} -For this subsection, we focus our attention on the \code{Statements} window on the upper right corner of the main menu. This window is presented as a table with an ``ID'' column and a ``Text'' column in which the text underlying a \dna\ Statement is displayed (see Figure~\ref{fig:statements}). - -There are three ways to navigate through statements. The first is displayed if you select the option \code{all} below the list of statements. As the name suggests, the window shows all statements, ordered by appearance in your database. The statements in the first document are on top, the statements in the last document you added are at the bottom of the table. By clicking on a statement you jump to the document and position it appears. - -The second option is called \code{current}. It provides a filter, so only the statements in the currently selected document are displayed in the Statements table. If you navigate to a different document, this selection will change. On top of the table, you should see the new statement you just created. If you haven't added or removed a statement before, the ID of the statement should be ``42''. - -The third option is called \code{filter}. When you choose this option, the ``Statements'' box increases in size and shows five new fields in which you can provide keywords to filter by for different fields in the \dna\ Statement: ID, person, organization, concept, agreement and a drop-down menu where you an switch between statement types. By entering, for instance, ``There should be legislation to regulate emissions.'' in the concept field, only statements regarding that concept will be displayed. Again, it is not necessary to provide the full text but it is sufficient to write in enough characters to differentiate the code clearly from other ones in the database. For example, if there would be a different concept called ``There should be legislation for cap and trade.'', then you would have to enter at least ``There should be legislation \textbf{t}'' before \dna\ can differentiate the two concepts. Or even easier, you could simply enter ``emissions'' to display only statements for which the concept contains the word ``emissions''. Additionally, you can again use regular expressions in the filter fields (see Section~\ref{subsubsec:adjregex}). For instance, if you type \code{1[2-5]} into the ID field, \dna\ will display all statements between 12 and 15. - -Instead of searching statements by just one variable, you can also combine filters. By entering ``There should be legislation to regulate emissions.'' in the concept field and ``Bob'' in the person field, only the \dna\ Statements regarding this specific concept and were made by Bob Slaughter---who is the only Bob in the database---are displayed. +For this subsection, we focus our attention on the \code{Statements} window on the upper right corner of the main menu. +This window is presented as a table with an ``ID'' column and a ``Text'' column in which the text underlying a \dna\ Statement is displayed (see Figure~\ref{fig:statements}). + +There are three ways to navigate through statements. +The first is displayed if you select the option \code{all} below the list of statements. +As the name suggests, the window shows all statements, ordered by appearance in your database. +The statements in the first document are on top, the statements in the last document you added are at the bottom of the table. +By clicking on a statement you jump to the document and position it appears. + +The second option is called \code{current}. +It provides a filter, so only the statements in the currently selected document are displayed in the Statements table. +If you navigate to a different document, this selection will change. +On top of the table, you should see the new statement you just created. +If you haven't added or removed a statement before, the ID of the statement should be ``42''. + +The third option is called \code{filter}. +When you choose this option, the ``Statements'' box increases in size and shows five new fields in which you can provide keywords to filter by for different fields in the \dna\ Statement: ID, person, organization, concept, agreement and a drop-down menu where you an switch between statement types. +By entering, for instance, ``There should be legislation to regulate emissions.'' in the concept field, only statements regarding that concept will be displayed. +Again, it is not necessary to provide the full text but it is sufficient to write in enough characters to differentiate the code clearly from other ones in the database. +For example, if there would be a different concept called ``There should be legislation for cap and trade.'', then you would have to enter at least ``There should be legislation \emph{t}'' before \dna\ can differentiate the two concepts. +Or even easier, you could simply enter ``emissions'' to display only statements for which the concept contains the word ``emissions''. +Additionally, you can again use regular expressions in the filter fields (see Section~\ref{subsubsec:adjregex}). +For instance, if you type \code{1[2-5]} into the ID field, \dna\ will display all statements between 12 and 15. + +Instead of searching statements by just one variable, you can also combine filters. +By entering ``There should be legislation to regulate emissions.'' in the concept field and ``Bob'' in the person field, only the \dna\ Statements regarding this specific concept and were made by Bob Slaughter---who is the only Bob in the database---are displayed. The filter fields all work in this way except \code{agreement} which only takes the values 0 for disagreement and 1 for agreement. \begin{figure} - \includegraphics[frame, width=\linewidth]{06-05-statements} + \includegraphics[width=\linewidth]{06-05-statements} \caption{Statements window in detail} \label{fig:statements} \end{figure} @@ -1404,16 +1632,25 @@ The filter fields all work in this way except \code{agreement} which only takes \section{Editing a Statements} \FloatBarrier -To edit a statement's details, you first need to select it, either by choosing it from the Statements table (see Figure~\ref{fig:statements}) or directly in the text. This will open the same window as in Figure~\ref{fig:statdetails} which we discussed in detail in Section~\ref{sec:createstat}. - -Besides that, you can also provide additional information for the variables in the \dna\ Statements. To find this menu you first have toggle the option to display a new window beneath the text window. To do that, find the view options in the top right corner of the main window (see Figure~\ref{fig:editdetails}, step 1). The three options you see here control how \dna\ looks or, more precisely, which menus are displayed. The left option displays/hides the ``Coder'' and ``Document properties'' menus, while the right one displays/hides the ``Statements'', ``Search within document'' and ``Regex highlighter'' menus. However, now we need the middle option which displays the mentioned field beneath the document text. +To edit a statement's details, you first need to select it, either by choosing it from the Statements table (see Figure~\ref{fig:statements}) or directly in the text. +This will open the same window as in Figure~\ref{fig:statdetails} which we discussed in detail in Section~\ref{sec:createstat}. + +Besides that, you can also provide additional information for the variables in the \dna\ Statements. +To find this menu you first have toggle the option to display a new window beneath the text window. +To do that, find the view options in the top right corner of the main window (see Figure~\ref{fig:editdetails}, step 1). +The three options you see here control how \dna\ looks or, more precisely, which menus are displayed. +The left option displays/hides the ``Coder'' and ``Document properties'' menus, while the right one displays/hides the ``Statements'', ``Search within document'' and ``Regex highlighter'' menus. +However, now we need the middle option which displays the mentioned field beneath the document text. \begin{figure} \includegraphics[width=\linewidth]{06-06-editdetails} \caption{Statements window in detail} \label{fig:editdetails} \end{figure} -In this window, you can make edits to persons, organizations or concepts in all \dna\ Statements at once, rather than to single statements. The advantage is that you do not have to edit each individual statement if you notice that you misspelt a name, that two concepts which you have coded actually represent the same idea or if you simply find a better concept name which adds some clarity. When you edit a concept (or person or organisation) in this menu, it is changed in all \dna\ Statements at once. When this menu is first opened, it contains no information before you select either \code{DNA Statement} or \code{Annotation} from the left drop-down menu (see Figure~\ref{fig:editstatm}). +In this window, you can make edits to persons, organizations or concepts in all \dna\ Statements at once, rather than to single statements. +The advantage is that you do not have to edit each individual statement if you notice that you misspelt a name, that two concepts which you have coded actually represent the same idea or if you simply find a better concept name which adds some clarity. +When you edit a concept (or person or organisation) in this menu, it is changed in all \dna\ Statements at once. +When this menu is first opened, it contains no information before you select either \code{DNA Statement} or \code{Annotation} from the left drop-down menu (see Figure~\ref{fig:editstatm}). \begin{figure} \centering \includegraphics[frame, width=0.6\linewidth]{06-07-editstatm} @@ -1421,32 +1658,59 @@ In this window, you can make edits to persons, organizations or concepts in all \label{fig:editstatm} \end{figure} -To provide additional information for persons, organizations or concepts you have to click on the label symbol in the top right corner of the same window (see Figure~\ref{fig:editdetails}, step 2). As in the other menu, the window contains no entries before you select if you want to edit statements or annotations from the left drop-down list (see Figure~\ref{fig:editdetails}, step 3). In the table presented now, you can add colour, type, alias and notes for each person, organization or concept. This information is not directly used in \dna\ but, as we will see in Chapter~\ref{chp:rdna}, can be used during analysis with \rdna. +To provide additional information for persons, organizations or concepts you have to click on the label symbol in the top right corner of the same window (see Figure~\ref{fig:editdetails}, step 2). +As in the other menu, the window contains no entries before you select if you want to edit statements or annotations from the left drop-down list (see Figure~\ref{fig:editdetails}, step 3). +In the table presented now, you can add colour, type, alias and notes for each person, organization or concept. +This information is not directly used in \dna\ but, as we will see in Chapter~\ref{chp:rdna}, can be used during analysis with \rdna. \FloatBarrier \section{Using the Regex Highlighter and Search Function} \label{sec:regex} -The last part of this section about coding statements in \dna\ describes how you can use the ``Regex highlighter'' and ``Search within document'' functions to help you quickly identify relevant parts of the documents you will be coding. Both functions are located on the right panel of the main window and can be folded or unfolded like every window in \dna\ (see Figure~\ref{fig:search}). - -We begin with the \code{Search within document} menu as it is what most people are already familiar with. By entering a search term in the text field, you can jump between all occurrences of that keyword in the current document in the same way as it works in popular text processing programs (such as MS Word) or in your web browser. You can test this by entering the term ``greenhouse effect'' and browse through the occurrences in Navin Nayak's hearing in the U.S. Congress (that is the second to last document in the database) with the left and right arrow buttons. As you might notice, all mentions of the greenhouse effect are fairly close together and Coder 1 has formatted a large part the section they are mentioned as \dna\ Statement. This is what will often happen during coding: as authors of a text or speakers will order their document or speech around sub-topics, the statements you wish to code can be close together. If you already know the most important keywords, it might therefore not be necessary to closely read the whole article or speech but can be more fruitful and efficient to jump between potential statements and only skim the remaining lines. - -One feature which sets the search function in \dna\ apart from other programs with which you are already familiar is again that it can take Regex expressions. One useful feature of Regex commands in this scenario is that you can use multiple keywords at the same time by putting the vertical bar character \code{|}, which represents the \textit{OR}, operator between them. You find this character next to the Shift button on your keyboard. So for instance, you could write ``global warming\textbf{|}climate change" to browse through all mentions of either of those words in the current document. Combining multiple keywords can serve as a quick way to browse through documents which are yet to code or which have already been coded to identify the most relevant parts. - -The \textbf{``Regex highlighter''} works in much the same way. But instead of browsing through the occurrences of a key term, you can change its font colour to a colour of your choice. Looking again at \textit{Figure~\ref{fig:search}}, you can see that multiple words have a different font colour: ``dioxide'' is orange, ``greenhouse'' is green, ``clima'' is blue and so on. This can help coders to notice when theory induced keywords appear in a paragraph. Again, it can be of help if you know a few basics about regular expressions, but as you can see, most of the keywords are written in plain English and you can use that as well if you prefer. However, consider that instead of the regular expression C[Oo0]2 you would have to enter both ``CO2'' and ``C02''. The Regex highlighter, just as the search function, is by default case insensitive. If you wish to highlight only specific cases of a word, you can put the option \code{(?-i)} at the beginning of your search string. +The last part of this section about coding statements in \dna\ describes how you can use the ``Regex highlighter'' and ``Search within document'' functions to help you quickly identify relevant parts of the documents you will be coding. +Both functions are located on the right panel of the main window and can be folded or unfolded like every window in \dna\ (see Figure~\ref{fig:search}). + +We begin with the \code{Search within document} menu as it is what most people are already familiar with. +By entering a search term in the text field, you can jump between all occurrences of that keyword in the current document in the same way as it works in popular text processing programs (such as MS Word) or in your web browser. +You can test this by entering the term ``greenhouse effect'' and browse through the occurrences in Navin Nayak's hearing in the U.S. +Congress (that is the second to last document in the database) with the left and right arrow buttons. +As you might notice, all mentions of the greenhouse effect are fairly close together and Coder 1 has formatted a large part the section they are mentioned as \dna\ Statement. +This is what will often happen during coding: as authors of a text or speakers will order their document or speech around sub-topics, the statements you wish to code can be close together. +If you already know the most important keywords, it might therefore not be necessary to closely read the whole article or speech but can be more fruitful and efficient to jump between potential statements and only skim the remaining lines. + +One feature which sets the search function in \dna\ apart from other programs with which you are already familiar is again that it can take Regex expressions. +One useful feature of Regex commands in this scenario is that you can use multiple keywords at the same time by putting the vertical bar character \code{|}, which represents the \emph{OR}, operator between them. +You find this character next to the Shift button on your keyboard. +So for instance, you could write ``global warming\textbf{|}climate change" to browse through all mentions of either of those words in the current document. +Combining multiple keywords can serve as a quick way to browse through documents which are yet to code or which have already been coded to identify the most relevant parts. + +The \emph{``Regex highlighter''} works in much the same way. +But instead of browsing through the occurrences of a key term, you can change its font colour to a colour of your choice. +Looking again at Figure~\ref{fig:search}, you can see that multiple words have a different font colour: ``dioxide'' is orange, ``greenhouse'' is green, ``clima'' is blue and so on. +This can help coders to notice when theory induced keywords appear in a paragraph. +Again, it can be of help if you know a few basics about regular expressions, but as you can see, most of the keywords are written in plain English and you can use that as well if you prefer. +However, consider that instead of the regular expression C[Oo0]2 you would have to enter both ``CO2'' and ``C02''. +The Regex highlighter, just as the search function, is by default case insensitive. +If you wish to highlight only specific cases of a word, you can put the option \code{(?-i)} at the beginning of your search string. \begin{figure} \includegraphics[width=\linewidth]{06-08-search} \caption{The Search and Regex highlighter functions} \label{fig:search} \end{figure} -This concludes the section about how to code statements in \dna. Even though this chapter turned out to be shorter than the two previous ones, this is where you will spend most of your time while using \dna. +This concludes the section about how to code statements in \dna. +Even though this chapter turned out to be shorter than the two previous ones, this is where you will spend most of your time while using \dna. \chapter{Exporting the Coded Data}\label{chp:dna-export} \chapterauthor{Johannes Gruber} \FloatBarrier -This section will walk you through the process of exporting data from \dna\ to continue analysis in different programs and provide detailed information about each of the 15 options you can change during export. If you intend to use \rdna\ to analyse your data---which is recommended---you will not have to export the data from \dna\ first as you can directly use the .dna database. However, \rdna's function \code{dna\_network} mirrors the options in the export window and hence it makes sense to familiarise yourself with the different ways in which networks can be exported from \dna. - -To open the window, simply open the drop-down menu ``Export'' and click on the only entry \code{Export network...}. This will open the export window as depicted in Figure~\ref{fig:exportwin}. The first thing you should do when you are not familiar with the different options is to tick the box \code{Display tooltips with instructions}. This will put some further information about each option on your screen when you rest your mouse cursor over one of them. +This section will walk you through the process of exporting data from \dna\ to continue analysis in different programs and provide detailed information about each of the 15 options you can change during export. +If you intend to use \rdna\ to analyse your data---which is recommended---you will not have to export the data from \dna\ first as you can directly use the .dna database. +However, \rdna's function \code{dna\_network} mirrors the options in the export window and hence it makes sense to familiarise yourself with the different ways in which networks can be exported from \dna. + +To open the window, simply open the drop-down menu ``Export'' and click on the only entry \code{Export network...}. +This will open the export window as depicted in Figure~\ref{fig:exportwin}. +The first thing you should do when you are not familiar with the different options is to tick the box \code{Display tooltips with instructions}. +This will put some further information about each option on your screen when you rest your mouse cursor over one of them. \begin{figure} \includegraphics[width=\linewidth]{07-01-exportwin} \caption{The export window} @@ -1455,9 +1719,17 @@ To open the window, simply open the drop-down menu ``Export'' and click on the o \section{Type of Network} -The first thing to consider is which type of network you want to export. There are three options: one-mode networks, two-mode networks and event lists. - -If you select to export a \textbf{``one-mode network''}, the resulting matrix will have the same nodes in the rows and columns (e.\,g., organizations x organizations) (see Table~\ref{tab:onemode}). The values in the cells in Table~\ref{tab:onemode} are a function of how often Variable 1 and Variable 2 are referenced together in \dna\ Statements. These values represent the edge weights of a network. All other options left on default, in the one-mode network case, that is the sum of all products of co-references by e.\,e., ogranisation A with organisation B (see Section~\ref{subsec:ignore}). Note, that the edge weight of an organisation with itself is always zero. One could also expect that these values would be aggregations of all statements an organisation made. However, this would not make theoretical sense as there is no edge between an organisation and itself. The the choice of the value zero in cells where row and column mention the same organisation are all zero is deliberate. +The first thing to consider is which type of network you want to export. +There are three options: one-mode networks, two-mode networks and event lists. + +If you select to export a \emph{``one-mode network''}, the resulting matrix will have the same nodes in the rows and columns (e.\,g., organizations $\times$ organizations) (see Table~\ref{tab:onemode}). +The values in the cells in Table~\ref{tab:onemode} are a function of how often Variable 1 and Variable 2 are referenced together in \dna\ Statements. +These values represent the edge weights of a network. +All other options left on default, in the one-mode network case, that is the sum of all products of co-references by e.\,e., ogranisation A with organisation B (see Section~\ref{subsec:ignore}). +Note, that the edge weight of an organisation with itself is always zero. +One could also expect that these values would be aggregations of all statements an organisation made. +However, this would not make theoretical sense as there is no edge between an organisation and itself. +The the choice of the value zero in cells where row and column mention the same organisation are all zero is deliberate. <>= #' prep environment @@ -1500,7 +1772,9 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", @ -A \textbf{``Two-mode network''}, on the other hand, has different sets of nodes in the rows and columns of the resulting matrix (e.\,g., concepts x organizations) (see Table~\ref{tab:twomode}). In this case, what you select in Variable 1 will become the rows of the matrix while Variable 2 will be the columns. In the two-mode network case, the edge weights will be, all other options left on default, simple counts of all co-references of Variable 1 and 2. +A \emph{``Two-mode network''}, on the other hand, has different sets of nodes in the rows and columns of the resulting matrix (e.\,g., concepts $\times$ organizations) (see Table~\ref{tab:twomode}). +In this case, what you select in Variable 1 will become the rows of the matrix while Variable 2 will be the columns. +In the two-mode network case, the edge weights will be, all other options left on default, simple counts of all co-references of Variable 1 and 2. <>= conn <- dna_connection(dna_sample()) dt <- dna_network(conn, @@ -1529,7 +1803,10 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", @ -The \textbf{``Event list''} is a little different from the other two options. Instead of summarising the statements over Variable 1 and 2, it simply lists all \dna\ Statements with each row containing all variables of a statement including the time which was set for the document a statement occurred in. The event list is thus a more detailed version of the statements window in the \dna\ user interface. As you can see in Table~\ref{tab:eventl}, this table is a lot larger than the matrices produced by the summarising algorithms used to produce one-mode and two node networks. +The \emph{``Event list''} is a little different from the other two options. +Instead of summarising the statements over Variable 1 and 2, it simply lists all \dna\ Statements with each row containing all variables of a statement including the time which was set for the document a statement occurred in. +The event list is thus a more detailed version of the statements window in the \dna\ user interface. +As you can see in Table~\ref{tab:eventl}, this table is a lot larger than the matrices produced by the summarising algorithms used to produce one-mode and two node networks. <>= conn <- dna_connection(dna_sample()) dt <- dna_network(conn, @@ -1561,14 +1838,21 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", \section{Statement Type} -There are usually two options for \textbf{``Statement type''} and you will probably never want to choose the second one---Annotations. The default is to export \dna\ Statements instead, which are the type that actually contains information worth exporting as a network. If you do wish to export your annotations, you will notice that the choices in Variable 1 and 2 are reduced to just the document variables: author, source, section and type. This is because the other variables, like concept or organization, do not exist in the type ``Annotation''. Thus the only option that really makes sense is to export annotations as event lists. +There are usually two options for \emph{``Statement type''} and you will probably never want to choose the second one---Annotations. +The default is to export \dna\ Statements instead, which are the type that actually contains information worth exporting as a network. +If you do wish to export your annotations, you will notice that the choices in Variable 1 and 2 are reduced to just the document variables: author, source, section and type. +This is because the other variables, like concept or organization, do not exist in the type ``Annotation''. +Thus the only option that really makes sense is to export annotations as event lists. -Choosing the statement type makes the most sense if you have created your own types while setting up the database (see Section~\ref{sec:stattype}). As outlined there, very are few scenarios exist in which you have more than one relevant statement type. +Choosing the statement type makes the most sense if you have created your own types while setting up the database (see Section~\ref{sec:stattype}). +As outlined there, very are few scenarios exist in which you have more than one relevant statement type. \section{File Format} -There are three diffrent file formats which can be used for export at the moment: .csv, .dl and .graphml. Alternativly, the data can be brought to \R\ using the \rdna\ pacakge to import data directly from a .dna file (see Chapter~\ref{chp:rdna}). +There are three diffrent file formats which can be used for export at the moment: .csv, .dl and .graphml. +Alternativly, the data can be brought to \R\ using the \rdna\ pacakge to import data directly from a .dna file (see Chapter~\ref{chp:rdna}). -The \code{.csv} format (short for comma-separated values) is basically a spreadsheet format in a text file. If you open it with a text editor, it will look something like this: +The \code{.csv} format (short for comma-separated values) is basically a spreadsheet format in a text file. +If you open it with a text editor, it will look something like this: <>= "";"Alliance to...";"Energy and E...";"Environmenta..."; "National Pet...";... "CO2 legislation will not hurt the economy.";0;2;1;2;2;2;1 @@ -1579,9 +1863,14 @@ The \code{.csv} format (short for comma-separated values) is basically a spread "There should be legislation to regulate emissions.";1;0;10;2;2;1;0 @ This is the exact same table as Table~\ref{tab:twomode}\footnote{Except that column names needed to be truncated to fit on this page.} -but instead of rows and columns, the values are stored in plain text, with each line containing one row of the table and the values separated by semicolons. You can usually open these files in MS Excel, LibreOffice, or Numbers (Apple's spreadsheet application) or other spreadsheet applications without any further steps. Note, however, that your spreadsheet application sometimes needs to be set to use semicolons to separate values instead of commas.\footnote{This is usually only a problem in MS Excel running on a Windows computer where the CSV separator is set system-wide in the language options. If you experience problems, you need to use the import function in Excel rather than opening the .csv file directly.} +but instead of rows and columns, the values are stored in plain text, with each line containing one row of the table and the values separated by semicolons. +You can usually open these files in MS Excel, LibreOffice, or Numbers (Apple's spreadsheet application) or other spreadsheet applications without any further steps. +Note, however, that your spreadsheet application sometimes needs to be set to use semicolons to separate values instead of commas.\footnote{This is usually only a problem in MS Excel running on a Windows computer where the CSV separator is set system-wide in the language options. +If you experience problems, you need to use the import function in Excel rather than opening the .csv file directly.} -\code{.dl} files are for use with the network analysis software \ucinet. Again, information in .dl files is stored in plain text and you can open the files using the text editor of your choice if you want to inspect the format in detail. Taking again Table~\ref{tab:twomode} as an example, the respective .dl file looks like this: +\code{.dl} files are for use with the network analysis software \ucinet. +Again, information in .dl files is stored in plain text and you can open the files using the text editor of your choice if you want to inspect the format in detail. +Taking again Table~\ref{tab:twomode} as an example, the respective .dl file looks like this: <>= dl nr = 6, nc = 7, format = fullmatrix @@ -1608,12 +1897,15 @@ data: 2 2 0 0 1 1 1 1 0 10 2 2 1 0 @ -\ucinet\ is a Windows application which also runs on Mac and Linux if you use it with and emulators such as Wine or Bootcamp. A 60-day free trial version with all features included is available for free on their website: -\url{https://sites.google.com/site/ucinetsoftware/downloads}. However, we advise to use either \visone\ or \R\ for visualising your networks as both are free, under active development and---in the case of \R---open source. - -%include screenshot? +\ucinet\ is a Windows application which also runs on Mac and Linux if you use it with and emulators such as Wine or Bootcamp. +A 60-day free trial version with all features included is available for free on their website: +\url{https://sites.google.com/site/ucinetsoftware/downloads}. +However, we advise to use either \visone\ or \R\ for visualising your networks as both are free, under active development and---in the case of \R---open source. -The \code{.graphml} format is based on the open standard XML and while still readable by humans, the output file for Table~\ref{tab:twomode} would be too long to display it here. .graphml files can be opened using \visone, which is ``a software tool intended for research and teaching in social network analysis'' (see \url{http://visone.info/html/about.html}). Since it is a \java\ program like \dna\ itself, it can be run on any operating system capable of installing \java---which means bascially all of them. You can take a glimpse at its visualisation capabilities in Figure~\ref{fig:visone}, which shows the plot of Table~\ref{tab:twomode}. +The \code{.graphml} format is based on the open standard XML and while still readable by humans, the output file for Table~\ref{tab:twomode} would be too long to display it here. +\code{.graphml} files can be opened using \visone, which is ``a software tool intended for research and teaching in social network analysis'' (see \url{http://visone.info/html/about.html}). +Since it is a \java\ program like \dna\ itself, it can be run on any operating system capable of installing \java---which means bascially all of them. +You can take a glimpse at its visualisation capabilities in Figure~\ref{fig:visone}, which shows the plot of Table~\ref{tab:twomode}. \begin{figure} \centering @@ -1625,9 +1917,19 @@ The \code{.graphml} format is based on the open standard XML and while still rea \section{Variable 1 and 2} As mentioned earlier, Variable 1 and 2 do different things depending on whether you select one-mode or two-mode under \code{Type of network}. -In a one-mode network, Variable 1 will contain the node class used both for the rows and columns of the matrix. For example, select the variable for organizations in order to export an organization $\times$ organization network such as shown in Table~\ref{tab:onemode}. Variable 2 in a one-node network will denote the variable through which the edges are aggregated (i.\,e., the values in the cells). For example, if you export a one-mode network of organizations, what makes the most sense is to aggregate how often they co-reference the same concept. That means that the second variable should be set to \code{concept}. - -In a two-mode network, the first variable denotes the node class for the rows, while the second variable denotes the node class used for the columns of the resulting network matrix. For Table~\ref{tab:twomode}, for example, we set \code{Variable 1} to \code{concept} and \code{Variable 1} to \code{organization}. Instead of seeing which concepts were referenced by which organisation, we could also create a table that displays person x concept. To do that we simply set \code{Variable 1} to \code{concept} and \code{Variable 2} to \code{person}. To make the logic underlying the use of the two variables even more clear we can also choose to create a somewhat redundent two-mode matrix. By setting \code{Variable 1} to \code{organization} and \code{Variable 2} to \code{person} we can count how often statements reference organisations and persons together. Since every person belongs to just one organisation, the resulting matrix will count all statements by a person in one cell of her/his column while the result of all other cells in her/his column is zero: +In a one-mode network, Variable 1 will contain the node class used both for the rows and columns of the matrix. +For example, select the variable for organizations in order to export an organization $\times$ organization network such as shown in Table~\ref{tab:onemode}. +Variable 2 in a one-node network will denote the variable through which the edges are aggregated (i.\,e., the values in the cells). +For example, if you export a one-mode network of organizations, what makes the most sense is to aggregate how often they co-reference the same concept. +That means that the second variable should be set to \code{concept}. + +In a two-mode network, the first variable denotes the node class for the rows, while the second variable denotes the node class used for the columns of the resulting network matrix. +For Table~\ref{tab:twomode}, for example, we set \code{Variable 1} to \code{concept} and \code{Variable 1} to \code{organization}. +Instead of seeing which concepts were referenced by which organisation, we could also create a table that displays person $\times$ concept. +To do that we simply set \code{Variable 1} to \code{concept} and \code{Variable 2} to \code{person}. +To make the logic underlying the use of the two variables even more clear we can also choose to create a somewhat redundent two-mode matrix. +By setting \code{Variable 1} to \code{organization} and \code{Variable 2} to \code{person} we can count how often statements reference organisations and persons together. +Since every person belongs to just one organisation, the resulting matrix will count all statements by a person in one cell of her/his column while the result of all other cells in her/his column is zero: <>= conn <- dna_connection(dna_sample()) dt <- dna_network(conn, @@ -1655,15 +1957,27 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", row_spec(0, angle = 90) @ -When you look at the column with Christine Todd Whitman in above's table, you can see that all of her statements co-reference the Environmental Protection Agency. This is, therefore, the organisation she belongs to. A table like that would be rarely useful in a research project though, except maybe for checking if there had been inconsistencies during the coding process. +When you look at the column with Christine Todd Whitman in above's table, you can see that all of her statements co-reference the Environmental Protection Agency. +This is, therefore, the organisation she belongs to. +A table like that would be rarely useful in a research project though, except maybe for checking if there had been inconsistencies during the coding process. \section{Qualifier and Qualifier Aggregation}\label{sec:qualifier} -The qualifier is a binary or integer variable which indicates different qualities or levels of association between variable 1 and variable 2. In many cases, the qualifier is binary, with the only possible outcomes being agreement and disagreement. However, the case could also be made to code different increments of agreement, for instance, by using a scale with -5 = strongly disagree to 5 = strongly agree. You already saw the qualifier in Section~\ref{sec:createstat} when we created a new statement and had to tick a box in order to indicate support or rejection of the chosen concept. +The qualifier is a binary or integer variable which indicates different qualities or levels of association between variable 1 and variable 2. +In many cases, the qualifier is binary, with the only possible outcomes being agreement and disagreement. +However, the case could also be made to code different increments of agreement, for instance, by using a scale with -5 = strongly disagree to 5 = strongly agree. +You already saw the qualifier in Section~\ref{sec:createstat} when we created a new statement and had to tick a box in order to indicate support or rejection of the chosen concept. -The combination of qualifier and qualifier aggregation determines which algorithm will be used to calculate the edge weights (see Chapter~\ref{chp:algorithms}). Again, this also depends on the chosen network type. In case of the event list, for instance, there is just one option: ignore. Choices for the other two network types are explained in the next two sub-sections. +The combination of qualifier and qualifier aggregation determines which algorithm will be used to calculate the edge weights (see Chapter~\ref{chp:algorithms}). +Again, this also depends on the chosen network type. +In case of the event list, for instance, there is just one option: ignore. +Choices for the other two network types are explained in the next two sub-sections. \subsection{One-mode Networks} -\textbf{Ignore.} This does the same as in two-mode networks: it ignores the qualifier and simply aggregates all co-references of Variable 1 and 2. As the ignore algorithm in \dna\ can be a little confusing for new users, this might be a good opportunity to complement Section~\ref{subsec:ignore} with an example. As you can see in Table~\ref{tab:onemode}, the edge weight between the Senate and the Sierra Club is seven. We can use Table~\ref{tab:disagree} to calculate this number by hand. +\begin{description} +\item[Ignore] This does the same as in two-mode networks: it ignores the qualifier and simply aggregates all co-references of Variable 1 and 2. +As the ignore algorithm in \dna\ can be a little confusing for new users, this might be a good opportunity to complement Section~\ref{subsec:ignore} with an example. +As you can see in Table~\ref{tab:onemode}, the edge weight between the Senate and the Sierra Club is seven. +We can use Table~\ref{tab:disagree} to calculate this number by hand. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) @@ -1733,9 +2047,13 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", row_spec(6, bold = T) @ -Each value in Table~\ref{tab:disagree} represents a speciic value in a three-dimensional array which was descibed in Chapter~\ref{chp:algorithms}. One of the $x_{ijk}$ values is, for example, the count for $i =$ \emph{``CO2 legislation will not hurt theeconomy.''}, $j =$ \emph{``Senate''} and $k =$ \textit{disgaree}. Look in Table~\ref{tab:disagree} to see that this specific value is 2. +Each value in Table~\ref{tab:disagree} represents a speciic value in a three-dimensional array which was descibed in Chapter~\ref{chp:algorithms}. +One of the $x_{ijk}$ values is, for example, the count for $i =$ \emph{``CO2 legislation will not hurt theeconomy.''}, $j =$ \emph{``Senate''} and $k =$ \emph{disgaree}. +Look in Table~\ref{tab:disagree} to see that this specific value is 2. -You can also see that the Senate and Sierra Club co-reference three concepts: `\emph{`CO2 legislation will not hurt the economy.''}, \emph{``Emissions legislation should regulate CO2.''} and \emph{``There should be legislation to regulate emissions.''}. The other three are not co-refenrced and are therefore not counted at all. For the co-referenced concepts, the edge weight is number of statments from Senate multiplied with number of statments from Sierra Club (see Equation~\ref{eq:ignore}; we are ignoring the normalisation for now): +You can also see that the Senate and Sierra Club co-reference three concepts: `\emph{`CO2 legislation will not hurt the economy.''}, \emph{``Emissions legislation should regulate CO2.''} and \emph{``There should be legislation to regulate emissions.''}. +The other three are not co-refenrced and are therefore not counted at all. +For the co-referenced concepts, the edge weight is number of statments from Senate multiplied with number of statments from Sierra Club (see Equation~\ref{eq:ignore}; we are ignoring the normalisation for now): \infobox{9cm}{ First, we calculate $\left( \sum_{k} x_{ijk} \right) \left( \sum_{k} x_{i'jk} \right)$ with $i = \text{Senate}$ and $i = \text{Sierra Club}$ for each concept j:\\ @@ -1752,7 +2070,12 @@ You can also see that the Senate and Sierra Club co-reference three concepts: `\ } -\textbf{Congruence.} This option is only available for one-mode networks. It means that only similarity or matches on the qualifier variable are counted in order to construct an edge. In case of a binary second variable (e.\,g., (dis-)agreement) this means that only statements are counted were, for example, two organisations co-support or both co-reject a concept. You can see how this changes the output when you compare Table~\ref{tab:onemode} and Table~\ref{tab:qual3}. Focusing again on the edge between the Senate and the Sierra Club, you can see now that the value dropped from seven to two as they do not support or reject all of the same concepts. We can repeat the same calculation, this time using Equation~\ref{eq:congruence_binary} from Section~\ref{subsec:congruence}: +\item[Congruence] This option is only available for one-mode networks. +It means that only similarity or matches on the qualifier variable are counted in order to construct an edge. +In case of a binary second variable (e.\,g., (dis-)agreement) this means that only statements are counted were, for example, two organisations co-support or both co-reject a concept. +You can see how this changes the output when you compare Table~\ref{tab:onemode} and Table~\ref{tab:qual3}. +Focusing again on the edge between the Senate and the Sierra Club, you can see now that the value dropped from seven to two as they do not support or reject all of the same concepts. +We can repeat the same calculation, this time using Equation~\ref{eq:congruence_binary} from Section~\ref{subsec:congruence}: \infobox{9cm}{ First, we calculate $\sum_{k} x_{ijk} x_{i'jk}$ for each concept $j$ and $k = \text{agreement}$ as well as $k = \text{disagreement}$:\\ @@ -1798,10 +2121,14 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", With an integer qualifier variable, the inverse of the absolute distance plus one (i.\,e., the proximity) is used instead of a match. -\textbf{Conflict.} Conflict is basically the opposite of congruence: while in the congruence network the matches (i.\,e., co-supported or co-rejected concepts) are counted, conflict counts only non-matches. With a binary qualifier, this means that organizations A and B are connected if one of them supports a concept and the other one rejects the concept. We can see how this plays out in Table~\ref{tab:qual4}. Taking the same example as above we can again calculate the edge weight of Senate and Sierra Club using Equation~\ref{eq:conflict_binary} from Section~\ref{subsec:conflict}: +\item[Conflict] Conflict is basically the opposite of congruence: while in the congruence network the matches (i.\,e., co-supported or co-rejected concepts) are counted, conflict counts only non-matches. +With a binary qualifier, this means that organizations A and B are connected if one of them supports a concept and the other one rejects the concept. +We can see how this plays out in Table~\ref{tab:qual4}. +Taking the same example as above we can again calculate the edge weight of Senate and Sierra Club using Equation~\ref{eq:conflict_binary} from Section~\ref{subsec:conflict}: \infobox{10cm}{ - First, we calculate $\sum_{k} x_{ijk} x_{i'jk'}$ for each concept $j$. To make that easier to follow, we calcuate $x_{ijk} x_{i'jk'}$ individually for the two possible cases: $k = \text{agreement}$ and $k' = \text{disagreement}$ as well as $k = \text{disagreement}$ and $k' = \text{agreement}$:\\ + First, we calculate $\sum_{k} x_{ijk} x_{i'jk'}$ for each concept $j$. +To make that easier to follow, we calcuate $x_{ijk} x_{i'jk'}$ individually for the two possible cases: $k = \text{agreement}$ and $k' = \text{disagreement}$ as well as $k = \text{disagreement}$ and $k' = \text{agreement}$:\\ Concept 1 ($k = \text{agreement;} k' = \text{disagreement}$): \hfill $0 \cdot 0 = 0$ \\ Concept 1 ($k = \text{disagreement;} k' = \text{agreement}$): \hfill $0 \cdot 0 = 0$ \\ @@ -1848,11 +2175,13 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", row_spec(0, angle = 90) @ -Note, that the result of the congruence network plus the result of the conflict network equals the outcome of the ignore algorithm. This is because the difference between congruence and conflict is the factor which is ignored in the ignore network and all cases are added up. +Note, that the result of the congruence network plus the result of the conflict network equals the outcome of the ignore algorithm. +This is because the difference between congruence and conflict is the factor which is ignored in the ignore network and all cases are added up. With an integer qualifier, the absolute distance is used instead (see Section~\ref{subsec:conflict}). -\textbf{Subtract.} If the ignore network can be defined as adding up the cases on congruence and conflict, subtract is the exact opposite: to calculate it, a congruence network and a conflicting network are created separately and then the conflict network ties are subtracted from the congruence network ties. Taking the example from above, the edge between Senate and Sierra Club would be calculated using above results: +\item[Subtract] If the ignore network can be defined as adding up the cases on congruence and conflict, subtract is the exact opposite: to calculate it, a congruence network and a conflicting network are created separately and then the conflict network ties are subtracted from the congruence network ties. +Taking the example from above, the edge between Senate and Sierra Club would be calculated using above results: \infobox{9cm}{ Congruence: $y_{ii'}^\text{congruence binary} = 2$\\ Conflict: $y_{ii'}^\text{conflict binary} = 5$\\ @@ -1861,7 +2190,9 @@ With an integer qualifier, the absolute distance is used instead (see Section~\r \centerline{\textbf{$2 - 5 = -3$}} } -See Table~\ref{tab:qual5} to check that this is correct. The meaning of this outcome is that Senate and Sierra Club do have in fact more differences than they have in common. You can also see that this is true for several of the other organisation pairs, suggesting a quite controversial discourse. +See Table~\ref{tab:qual5} to check that this is correct. +The meaning of this outcome is that Senate and Sierra Club do have in fact more differences than they have in common. +You can also see that this is true for several of the other organisation pairs, suggesting a quite controversial discourse. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) dt <- dna_network(conn, @@ -1888,12 +2219,21 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", kable_styling(latex_options = c("striped", "scale_down", "HOLD_position")) %>% row_spec(0, angle = 90) @ +\end{description} \subsection{Two-mode (Affiliation) Networks} - -\textbf{Ignore.} The agreement qualifier variable is ignored, i.e., the network is constructed as if all values on the qualifier variable were the same. In the most common case, the qualifier being (dis-)agreement, this means that co-references of a concept are aggregated, no matter if persons or organisations agree on them or not (see Table~\ref{tab:onemode}). The way in which the edge weights are constructed was already mentioned in Section~\ref{sec:twomode}. In the simplest case, a two-mode network with a binary qualifier, the edge weights for ignore are simple counts of co-references of variable 1 and 2. - -\textbf{Subtract.} If the qualifier is a regular binary (dis-)agreement value, all disagreeing statements will be subtracted from all agreeing statements. For example, if an organisation mentions a concept two times in a positive way and three times in a negative way, there will be an edge weight of -1 between the organization and the concept. You can see how this plays out for the sample file in Table~\ref{tab:qual}. The \emph{National Petrochemical \& Refiners Association}, for example, disagreed twice to both \emph{``CO2 legislation will not hurt the economy''} and \emph{``There should be legislation to regulate emissions.''} resulting in edge weights of -2 for both concepts. If the qualifier is an integer value, subtract basically does the same: the absolute values of the negative qualifier codes are subtracted from the positive ones. In the example from above, if an organisation agrees somewhat (+1) to a concept twice and then disagrees strongly (-2) to the same concept twice, the edge weight would be -2. +\begin{description} +\item[Ignore] The agreement qualifier variable is ignored, i.e., the network is constructed as if all values on the qualifier variable were the same. +In the most common case, the qualifier being (dis-)agreement, this means that co-references of a concept are aggregated, no matter if persons or organisations agree on them or not (see Table~\ref{tab:onemode}). +The way in which the edge weights are constructed was already mentioned in Section~\ref{sec:twomode}. +In the simplest case, a two-mode network with a binary qualifier, the edge weights for ignore are simple counts of co-references of variable 1 and 2. + +\item[Subtract] If the qualifier is a regular binary (dis-)agreement value, all disagreeing statements will be subtracted from all agreeing statements. +For example, if an organisation mentions a concept two times in a positive way and three times in a negative way, there will be an edge weight of -1 between the organization and the concept. +You can see how this plays out for the sample file in Table~\ref{tab:qual}. +The \emph{National Petrochemical \& Refiners Association}, for example, disagreed twice to both \emph{``CO2 legislation will not hurt the economy''} and \emph{``There should be legislation to regulate emissions.''} resulting in edge weights of -2 for both concepts. +If the qualifier is an integer value, subtract basically does the same: the absolute values of the negative qualifier codes are subtracted from the positive ones. +In the example from above, if an organisation agrees somewhat (+1) to a concept twice and then disagrees strongly (-2) to the same concept twice, the edge weight would be -2. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) dt <- dna_network(conn, @@ -1922,7 +2262,12 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", row_spec(0, angle = 90) @ -\textbf{Combine.} This option is only available for two-mode networks. Instead of doing mathematical operations on the qualifier values, combine creates a set of qualitative categories. In the case of a organization x concept matrix, there would be four possible outcomes: If an organsation neither disagrees nor agrees (i.\,e. never references the concept at all) the value would be 0; if the organisation always agreed on the concept whenever it mentioned it, the value is 1; if the organisation always disagreed on the concept whenever it mentioned it, the value is 2; and when they reference a statment both in a positve and negative (i.\,e. when heir stance towards it is mixed or ambiguous), the edge value is 3. You can see this in Table~\ref{tab:qual2}. With an integer variable, this may become more complex. As more combinations are possible and hence more qualitative categories need to be created (see Section~\ref{sec:twomode}. +\item[Combine] This option is only available for two-mode networks. +Instead of doing mathematical operations on the qualifier values, combine creates a set of qualitative categories. +In the case of a organization $\times$ concept matrix, there would be four possible outcomes: If an organsation neither disagrees nor agrees (i.\,e., never references the concept at all) the value would be 0; if the organisation always agreed on the concept whenever it mentioned it, the value is 1; if the organisation always disagreed on the concept whenever it mentioned it, the value is 2; and when they reference a statment both in a positve and negative (i.\,e., when heir stance towards it is mixed or ambiguous), the edge value is 3. +You can see this in Table~\ref{tab:qual2}. +With an integer variable, this may become more complex. +As more combinations are possible and hence more qualitative categories need to be created (see Section~\ref{sec:twomode}. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) dt <- dna_network(conn, @@ -1950,27 +2295,48 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", column_spec(3, bold = T) %>% row_spec(0, angle = 90) @ - +\end{description} \section{Normalization}\label{sec:normal} -In most real-life networks, normalisation is important. The reason is that some actors are more salient than others in public discussion. Government officials in charge of a certain problem will usually be covered more intensely than public interest groups who have an opposite stance. Other actors, such as political parties, follow a membership logic according to which they are by definition more diverse than others with regard to opinions. That means that due to their activity and diversity, these actors have agreement or disagreement ties to most other actors in the network at some point. This can obscure the real structure of a network and make it much harder to identify coalitions \citep{leifeld2017discourse}. - -To cancel out this activity effect, one can divide the edge weight between two organisations by a function of the two organizations' activity or frequency of making statements (see Section~\ref{sec:normalis}). This normalization procedure leaves us with a network of edge weights that reflect similarity in opinions without taking into account centrality or activity. Once again, which options are available depends on the network type. Only the option \code{no} is available in both types---which switches off normalization and is the default value. +In most real-life networks, normalisation is important. +The reason is that some actors are more salient than others in public discussion. +Government officials in charge of a certain problem will usually be covered more intensely than public interest groups who have an opposite stance. +Other actors, such as political parties, follow a membership logic according to which they are by definition more diverse than others with regard to opinions. +That means that due to their activity and diversity, these actors have agreement or disagreement ties to most other actors in the network at some point. +This can obscure the real structure of a network and make it much harder to identify coalitions \citep{leifeld2017discourse}. + +To cancel out this activity effect, one can divide the edge weight between two organisations by a function of the two organizations' activity or frequency of making statements (see Section~\ref{sec:normalis}). +This normalization procedure leaves us with a network of edge weights that reflect similarity in opinions without taking into account centrality or activity. +Once again, which options are available depends on the network type. +Only the option \code{no} is available in both types---which switches off normalization and is the default value. \begin{itemize} \item \textbf{Two-mode network} - \begin{itemize} - \item \textbf{Activity.} This divides the edge weights through the activity of the node from the first variable. For example, in and concept x organisation network in which organisation A has made four statements in total, the edge with concept B, which A mentioned once, has the value 0.25. - \item \textbf{Prominence.} This divides the edge weights through the prominence of the node from the second variable. For example, in and concept x organisation network in which concept B was mentioned eight times by all organisations and once by organisation A, the edge of A and B has the value 0.125. - \end{itemize} + \begin{description} + \item[Activity] This divides the edge weights through the activity of the node from the first variable. +For example, in and concept $\times$ organisation network in which organisation A has made four statements in total, the edge with concept B, which A mentioned once, has the value 0.25. + \item[Prominence] This divides the edge weights through the prominence of the node from the second variable. +For example, in and concept $\times$ organisation network in which concept B was mentioned eight times by all organisations and once by organisation A, the edge of A and B has the value 0.125. + \end{description} \item \textbf{One-mode network} - \begin{itemize} - \item \textbf{Average activity.} Average activity divides edge weights between first-variable nodes by the average number of different second-variable nodes they are adjacent with in a two-mode network. For example, if organization A makes statements about 20 different concepts and B makes statements about 60 different concepts, the edge weight between A and B in the congruence network is divided by 40. To achieve a better scaling, all edge weights in the resulting normalized one-mode network matrix are scaled between 0 and 1. The respective algorithm can be found in Equation~\ref{eq:activity}. - \item \textbf{Jaccard similarity.} Jaccard similarity is a similarity measure with known normalizing properties. In contrast to \code{average activity}, it divides the co-occurrence frequency by the activity count of both separate actors plus their joint activity. The algorithm used for this normalisation can be found in Equation~\ref{eq:jaccard}. - \item \textbf{Cosine similarity.} Cosine similarity is another similarity measure with normalizing properties. It divides edge weights by the product of the nodes' activity. Find this algorithm in Equation~\ref{eq:cosine}. - \end{itemize} + \begin{description} + \item[Average activity] Average activity divides edge weights between first-variable nodes by the average number of different second-variable nodes they are adjacent with in a two-mode network. +For example, if organization A makes statements about 20 different concepts and B makes statements about 60 different concepts, the edge weight between A and B in the congruence network is divided by 40. +To achieve a better scaling, all edge weights in the resulting normalized one-mode network matrix are scaled between 0 and 1. +The respective algorithm can be found in Equation~\ref{eq:activity}. + \item[Jaccard similarity] Jaccard similarity is a similarity measure with known normalizing properties. +In contrast to \code{average activity}, it divides the co-occurrence frequency by the activity count of both separate actors plus their joint activity. +The algorithm used for this normalisation can be found in Equation~\ref{eq:jaccard}. + \item[Cosine similarity] Cosine similarity is another similarity measure with normalizing properties. +It divides edge weights by the product of the nodes' activity. +Find this algorithm in Equation~\ref{eq:cosine}. + \end{description} \end{itemize} -Normalisation can be used in the different networks described in Section~\ref{sec:qualifier} to correct potential biases introduced by very active nodes. By using a threshold value on the edge weights before visualising the network, normalisation can make it easier to remove low-intensity ties without discriminating against organisations with a low media profile. Furthermore, the two normalisation algorithm which are based on vector similarities (Cosine and Jaccard) prepare networks to be fed into hierarchical cluster analyses, nonmetric multidimensional scaling, or other clustering techniques that are based on distance or similarity measures in order to identify coalitions in a policy debate as an alternative to community detection. Details about normalisation can be found in \citet{leifeld2017discourse}. In Table~\ref{tab:normal} you can see what how the two-mode network from Table~\ref{tab:twomode} looks like after applying the activity normalisation algorithm. +Normalisation can be used in the different networks described in Section~\ref{sec:qualifier} to correct potential biases introduced by very active nodes. +By using a threshold value on the edge weights before visualising the network, normalisation can make it easier to remove low-intensity ties without discriminating against organisations with a low media profile. +Furthermore, the two normalisation algorithm which are based on vector similarities (Cosine and Jaccard) prepare networks to be fed into hierarchical cluster analyses, nonmetric multidimensional scaling, or other clustering techniques that are based on distance or similarity measures in order to identify coalitions in a policy debate as an alternative to community detection. +Details about normalisation can be found in \citet{leifeld2017discourse}. +In Table~\ref{tab:normal} you can see what how the two-mode network from Table~\ref{tab:twomode} looks like after applying the activity normalisation algorithm. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) @@ -2002,15 +2368,23 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", \section{Duplicates} -The next option in the export window would be \code{Isolates}, but as you will see, it makes more sense to talk about that option last. The background of the Duplicates feature is that multiple statements from the same person or organisation referring to the same statement do not always indicate stronger agreement or disagreement. -For removing duplicates, there are again several options. This time, these are independent of your other choices in the export window: +The next option in the export window would be \code{Isolates}, but as you will see, it makes more sense to talk about that option last. +The background of the Duplicates feature is that multiple statements from the same person or organisation referring to the same statement do not always indicate stronger agreement or disagreement. +For removing duplicates, there are again several options. +This time, these are independent of your other choices in the export window: -\begin{itemize} - \item \textbf{Include all duplicates.} By default, all statements are included in a network export. - \item \textbf{Ignore per document.} This removes duplicated statements which occur in the same document. In a newspaper article, for example, the number of times an actor is quoted with a statement may be a function of the journalist's agenda or the reporting style of the news media outlet, rather than the actor's deliberate attempt to speak multiple times about a specific topic. In these cases it makes sense to remove all duplicated statements in this article. - \item \textbf{Ignore per calendar week/month/year.} In cases in which one or several newspapers reprint interviews, quotes or reports multiple times in different documents, it might make sense to remove these artefacts over time rather than on a document level. - \item \textbf{Ignore across date range.} This removes all duplicated statements in all documents in the database. Consequently, edge weights of the different networks are converted to 1 if there has been co-reference or co-rejection or 0 if there has not. Usually, \code{Ignore across date range.} therefore converts the network into a boolean matrix. However, as you can see in Table~\ref{tab:dupl}, there is one 2 value at the edge of ``Energy and Environmental Analysis, Inc.'' and ``Emissions legislation should regulate CO2.''. This happened because this organisation contradicted itself by expressing both agreement and disagreement during the hearings. - \end{itemize} +\begin{description} + \item[Include all duplicates] By default, all statements are included in a network export. + \item[Ignore per document] This removes duplicated statements which occur in the same document. +In a newspaper article, for example, the number of times an actor is quoted with a statement may be a function of the journalist's agenda or the reporting style of the news media outlet, rather than the actor's deliberate attempt to speak multiple times about a specific topic. +In these cases it makes sense to remove all duplicated statements in this article. + \item[Ignore per calendar week/month/year] In cases in which one or several newspapers reprint interviews, quotes or reports multiple times in different documents, it might make sense to remove these artefacts over time rather than on a document level. + \item[Ignore across date range] This removes all duplicated statements in all documents in the database. +Consequently, edge weights of the different networks are converted to 1 if there has been co-reference or co-rejection or 0 if there has not. +Usually, \code{Ignore across date range.} therefore converts the network into a boolean matrix. +However, as you can see in Table~\ref{tab:dupl}, there is one 2 value at the edge of ``Energy and Environmental Analysis, Inc.'' and ``Emissions legislation should regulate CO2.''. +This happened because this organisation contradicted itself by expressing both agreement and disagreement during the hearings. +\end{description} Again we apply this transformation to Table~\ref{tab:twomode} to illustrate how the resulting matrix is affected: <>= @@ -2042,11 +2416,22 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", \section{Time Series Options} -The options for time series are controlled by the four fields in the fourth row of the export window. \code{Include from} and \code{Include until} can be used to narrow down the number of documents which are included. The date and time which matter here are not when the \dna\ Statement was coded, but when the statement was made, which means the date set in the metadata of the document it occurred in. The standard values are the time and date of the oldest and newest document in the database, respectively. If you set, for example, \code{Include from} to ``2005-01-27 - 00:00:00'' the document titled ``109-876: Bluestein, Joel-BUS-Y'' will be excluded as this hearing was held one day earlier. - -\textbf{\code{Moving time window}}, when set to anything other than the default \code{no time window}, \dna\ will create multiple overlapping time slices that are moved forward along the time axis. For each time slice, the network will be constructed and exported as an individual file. The statements in the sample database were made over a short period of time which leaves us only with the short slice units---seconds, minutes, hours and days---and windows for experimenting. However, this is sufficient to emphasize how times series are exported in \dna. - -You could, for example, be interested in a fast moving debate with actors changing opinions and/or sides daily. In this case, you could set \code{Moving time window} to \code{using days} and \code{time window size} to one. Consequently, \dna\ would export one network per day. These networks do not necessarily feature all organisations or concepts but will only show active nodes, as you can see in Table~\ref{tab:time}. Since there were only hearings on five of the selected 20 days (we excluded January 26th in the last step), the remaining 15 matrices are even completely empty. +The options for time series are controlled by the four fields in the fourth row of the export window. +\code{Include from} and \code{Include until} can be used to narrow down the number of documents which are included. +The date and time which matter here are not when the \dna\ Statement was coded, but when the statement was made, which means the date set in the metadata of the document it occurred in. +The standard values are the time and date of the oldest and newest document in the database, respectively. +If you set, for example, \code{Include from} to ``2005-01-27 - 00:00:00'' the document titled ``109-876: Bluestein, Joel-BUS-Y'' will be excluded as this hearing was held one day earlier. + +\code{Moving time window}, when set to anything other than the default \code{no time window}, \dna\ will create multiple overlapping time slices that are moved forward along the time axis. +For each time slice, the network will be constructed and exported as an individual file. +The statements in the sample database were made over a short period of time which leaves us only with the short slice units---seconds, minutes, hours and days---and windows for experimenting. +However, this is sufficient to emphasize how times series are exported in \dna. + +You could, for example, be interested in a fast moving debate with actors changing opinions and/or sides daily. +In this case, you could set \code{Moving time window} to \code{using days} and \code{time window size} to one. +Consequently, \dna\ would export one network per day. +These networks do not necessarily feature all organisations or concepts but will only show active nodes, as you can see in Table~\ref{tab:time}. +Since there were only hearings on five of the selected 20 days (we excluded January 26th in the last step), the remaining 15 matrices are even completely empty. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) dt <- dna_network(conn, @@ -2115,7 +2500,7 @@ kable(dt20, format = "latex", booktabs = T) %>% \rowcolors{3}{white}{white} %rowcolors turned off \begin{table}[H] -\caption{Time series two-mode networks (organizations x concept) (only three of five active days are included)\label{tab:time}} +\caption{Time series two-mode networks (organizations $\times$ concept) (only three of five active days are included)\label{tab:time}} \centering \begin{tabu} to 0.6\linewidth {>{\raggedright\arraybackslash}p{5cm}>{\raggedleft}X>{\raggedleft}X>{\raggedleft}X} \toprule @@ -2154,12 +2539,25 @@ kable(dt20, format = "latex", booktabs = T) %>% \end{table} \end{knitrout} -In this special case, time slices are non-overlapping since it is moved one day at a time. However, if we would select two or a higher number in \code{time window size}, slices would overlap by the chosen time unit. For example, if there had been hearings on the first, second and third of February, a network would be created for the first and second February and a second network would feature statements from the second and third. If there were more dates included in the time range, this process would continue until the end of the time period is reached. Other time units work in the same way. To get mutually exclusive (i.e., non-overlapping) time slices, the user should select them manually from the output. For example, if the window size is 10 days, you could only select file number one, eleven, 21 and so on. - -Instead of time units, it is also possible to use \textbf{event time}. This will create time slices of exactly 100 statement events, for example. However, it is possible that multiple events have identical timestamps. In this case, the resulting network time slice is more inclusive and also contains those statements that happened at the same time. +In this special case, time slices are non-overlapping since it is moved one day at a time. +However, if we would select two or a higher number in \code{time window size}, slices would overlap by the chosen time unit. +For example, if there had been hearings on the first, second and third of February, a network would be created for the first and second February and a second network would feature statements from the second and third. +If there were more dates included in the time range, this process would continue until the end of the time period is reached. +Other time units work in the same way. +To get mutually exclusive (i.e., non-overlapping) time slices, the user should select them manually from the output. +For example, if the window size is 10 days, you could only select file number one, eleven, 21 and so on. + +Instead of time units, it is also possible to use \code{event time}. +This will create time slices of exactly 100 statement events, for example. +However, it is possible that multiple events have identical timestamps. +In this case, the resulting network time slice is more inclusive and also contains those statements that happened at the same time. \section{Exclude from Variable} -The last row in the export window includes options which can be used to exclude statements which reference certain values. This can make sense if you are, for example, only interested in a certain kind of organisation. To include only NGOs in your network, you could select organization from \code{Exclude from variable} and then while holding the Ctrl key select ``Energy and Environmental Analysis, Inc.'', ``Environmental Protection Agency'', ``National Petrochemical \& Refiners Association'' and ``Senate'' from the list on the right. The preview will now show which nodes are excluded. The exported network will miss all statements which reference one of these organisations and only contains statements made by NGOs: +The last row in the export window includes options which can be used to exclude statements which reference certain values. +This can make sense if you are, for example, only interested in a certain kind of organisation. +To include only NGOs in your network, you could select organization from \code{Exclude from variable} and then while holding the Ctrl key select ``Energy and Environmental Analysis, Inc.'', ``Environmental Protection Agency'', ``National Petrochemical \& Refiners Association'' and ``Senate'' from the list on the right. +The preview will now show which nodes are excluded. +The exported network will miss all statements which reference one of these organisations and only contains statements made by NGOs: <>= conn <- dna_connection(dna_sample(verbose = FALSE)) dt <- dna_network(conn, @@ -2190,13 +2588,21 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", caption = "Two-mode row_spec(0, angle = 90) @ -Another common application for this feature is to exclude concepts which are very general and do not add to the structure of the discourse network. This will be shown in Section~\ref{sec:retnet} where one concept makes the difference between a fairly convoluted and a much more telling network visualisation. +Another common application for this feature is to exclude concepts which are very general and do not add to the structure of the discourse network. +This will be shown in Section~\ref{sec:retnet} where one concept makes the difference between a fairly convoluted and a much more telling network visualisation. \section{Isolates} -We saved isolates for last because now that all non-NGOs are removed from the export, it is easier to explain what this option does. If you look again at Figure~\ref{tab:exclud}, you will notice that not only are the edge weights smaller than before the exclusion, the non-NGO organisation nodes are gone as well. If one of the concepts would have never been referenced by any of the NGOs, this concept would be gone as well. This is because by default only nodes that show at least minimal activity are included in the exported networks. -As you can also see in Table~\ref{tab:time}, exclusion of statements can lead to very differently sized matrices. However, if you have ever manually merged matrices of different sizes, you will know that it can be tedious to get everything into the right form. In these situations, it is easier to merge multiple networks if they have the same matrix dimensions. To achieve compatibility of the matrix dimensions anyway, it is possible to include all nodes of the selected variable(s) in the whole database, irrespective of time, qualifiers, and excluded values (but without any edge weights larger than 0, i.e., as isolates). You can see this in Table~\ref{tab:isolates} which mirrors the information of Table~\ref{tab:exclud} but has the same dimensions as, for example, Table~\ref{tab:twomode}. +We saved isolates for last because now that all non-NGOs are removed from the export, it is easier to explain what this option does. +If you look again at Figure~\ref{tab:exclud}, you will notice that not only are the edge weights smaller than before the exclusion, the non-NGO organisation nodes are gone as well. +If one of the concepts would have never been referenced by any of the NGOs, this concept would be gone as well. +This is because by default only nodes that show at least minimal activity are included in the exported networks. +As you can also see in Table~\ref{tab:time}, exclusion of statements can lead to very differently sized matrices. +However, if you have ever manually merged matrices of different sizes, you will know that it can be tedious to get everything into the right form. +In these situations, it is easier to merge multiple networks if they have the same matrix dimensions. +To achieve compatibility of the matrix dimensions anyway, it is possible to include all nodes of the selected variable(s) in the whole database, irrespective of time, qualifiers, and excluded values (but without any edge weights larger than 0, i.e., as isolates). +You can see this in Table~\ref{tab:isolates} which mirrors the information of Table~\ref{tab:exclud} but has the same dimensions as, for example, Table~\ref{tab:twomode}. <>= conn <- dna_connection(dna_sample(verbose = FALSE)) @@ -2229,7 +2635,9 @@ kable(dt, format = "latex", booktabs = TRUE, linesep = "", row_spec(0, angle = 90) @ -As became clear in this section, the many options in \dna\ during export allow for an effective preparation pof you data for further analysis. Fromt the created network tables it is often already possible to draw some cautious inferences. From Table~\ref{tab:qual5}, for instance, it already became clear, that there is more conflict than congruence between several of the actors, such as between Senate and Sierra Club. +As became clear in this section, the many options in \dna\ during export allow for an effective preparation pof you data for further analysis. +From the created network tables it is often already possible to draw some cautious inferences. +From Table~\ref{tab:qual5}, for instance, it already became clear, that there is more conflict than congruence between several of the actors, such as between Senate and Sierra Club. <>= unlink(dna_sample()) @ @@ -2292,7 +2700,8 @@ To ensure that the following results can be reproduced exactly, we should set th set.seed(12345) @ -Now we are able to use the package. The first step is to initialize \dna. +Now we are able to use the package. +The first step is to initialize \dna. Out of the box, \rdna\ does not know where the \dna\ \texttt{.jar} file is located. We need to register \dna\ with \rdna\ to use them together. To do that, one needs to save the \dna\ \texttt{.jar} file to the working directory of the current \R\ session and then initialize \dna\ as follows (with \texttt{dna-2.0-beta20.jar} in this example): @@ -2308,7 +2717,9 @@ dna_gui() @ Alternatively, we can provide the file name of a local \dna\ database as an argument, and the database will be opened in \dna. -For example, we could open the \texttt{sample.dna} database which comes with the package. To that, we included a convenience function called \code{dna\_sample}. You can use this function in one of two ways: either, you use it to copy the sample database into your current working directory, from where \R\ can easily find it, or you use it directly in the package folder or \rdna: +For example, we could open the \texttt{sample.dna} database which comes with the package. +To that, we included a convenience function called \code{dna\_sample}. +You can use this function in one of two ways: either, you use it to copy the sample database into your current working directory, from where \R\ can easily find it, or you use it directly in the package folder or \rdna: <>= # copy sample.dna to your working directory and then open it via dna_gui dna_sample() @@ -2384,7 +2795,8 @@ congruence <- dna_network(conn, The result is an organization $\times$ organization matrix, where the cells represent on how many concepts any two actors (i\,e., the row organization and the column organization) had the same issue stance (by values of the qualifier variable \code{agreement}). The arguments of the \code{dna\_network} function resemble the options in the \dna\ export window. -Details on the various arguments of the function can be obtained by displaying the help page (\code{?dna\_network}). In the code chunk above, \code{statementType = "DNA Statement"} indicates which statement type should be used for the network export. +Details on the various arguments of the function can be obtained by displaying the help page (\code{?dna\_network}). +In the code chunk above, \code{statementType = "DNA Statement"} indicates which statement type should be used for the network export. In this case, the statement type \texttt{\dna\ Statement} contains the variables \code{organization}, \code{concept}, and \code{agreement}. The argument \code{qualifierAggregation = "congruence"} causes \rdna\ to count how often the unique elements of \code{variable1} have an identical value on the \code{qualifier} variable (here: \code{agreement}) when they refer to a concept (\code{variable2}). @@ -2417,7 +2829,8 @@ dna_plotCentrality(conn, of = "concept", fontSize = 10) @ -It looks like the the concept ``There should be legislation to regulate emissions.'' is in fact very consensual. By repeating the same command with a few different options we can check if the organizations do in fact all agree on this matter: +It looks like the the concept ``There should be legislation to regulate emissions.'' is in fact very consensual. +By repeating the same command with a few different options we can check if the organizations do in fact all agree on this matter: <>= dna_plotCentrality(conn, of = "organization", @@ -2426,7 +2839,8 @@ dna_plotCentrality(conn, "There should be legislation to regulate emissions."), invertValues = TRUE) @ -Instead of plotting agreement towards the concept, \code{of = "organization"} shows how often organizations agreed or disagreed with any statements. Yet, by combining \code{excludeValues} and \code{invertValues = TRUE}, we tell \R\ to \emph{only} regard the statement we want to look at. +Instead of plotting agreement towards the concept, \code{of = "organization"} shows how often organizations agreed or disagreed with any statements. +Yet, by combining \code{excludeValues} and \code{invertValues = TRUE}, we tell \R\ to \emph{only} regard the statement we want to look at. The plot shows that everyone but the ``National Petrochemical \& Refiners Association'' agrees to the concept we chose, which indicates that consnesus on the statement ``There should be legislation to regulate emissions.'' obfuscates the real structure of the network. Therefore we should exclude it from the congruence network. 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