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TorfsBot

Twitterbot automatically imitating Rik Torfs's tweets using interpolated Markov models and dynamic templates, live on Twitter on @TorfsBot.

Set-up

Training data

Due to copyright reasons, the tweets & columns used for training the bot can not be distributed. However, you can acquire such data yourself or use completely different source material and put them in \src\main\resources\torfstweets.txt and \src\main\resources\torfscolumns.txt. Both are required to just be new-line separated plain texts, without any mark-up or annotations. To download tweets, you can use this script. For the columns, just pasting the text into the torfscolumns.txt will do the trick.

Dependencies

The following repositories need to be cloned in folders next to this repository, as they are dependencies of this project:

Twitter connection

While you can run the bots without Twitter, running the main class will require a Twitter connection set-up through the environment to run from. For more information on how to run these type of bots, see twitter-util.

You will need to provide the following values in your environment (which can easily be set when running the code from an editor like IntellJ):

oauth.accessToken=
oauth.accessTokenSecret=
oauth.consumerKey=
oauth.consumerSecret=

Running

Run the bot by running be.thomaswinters.twitter.torfsbot.TorfsBot and giving as argument -debug.

Citation

To cite TorfsBot in an academic paper, the following BibTex entry to the paper (page 181) can be used:

@inproceedings{winters2019torfsbot,
  author = {Winters, T},
  booktitle = {31st European Summer School in Logic, Language and Information Student Session Proceedings},
  month = {Aug},
  pages = {181-189},
  organization = {Riga, Latvia},
  publisher = {ESSLLI},
  title = {Generating Philosophical Statements using Interpolated Markov Models and Dynamic Templates},
  year = {2019},
  startyear = {2019},
  startmonth = {Aug},
  startday = {5},
  finishyear = {2019},
  finishmonth = {Aug},
  finishday = {16},
  language = {English},
  conference = {European Summer School in Logic, Language and Information},
  day = {5},
  publicationstatus = {online-published},
}

Or as: Winters T. (2019) Imitating Philosophical Statements using Stacked Markov Chains and Dynamic Templates, In: 31st European Summer School in Logic, Language and Information (ESSLLI2019): Student Session, University of Latvia

About

🤖🐦 Twitterbot automatically imitating Rik Torfs's tweets using interpolated Markov models and dynamic templates

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