superuser_graph.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Warning message:\n",
      "\"package 'data.table' was built under R version 3.3.3\"Warning message:\n",
      "\"package 'dplyr' was built under R version 3.3.2\"------------------------------------------------------------------------------\n",
      "data.table + dplyr code now lives in dtplyr.\n",
      "Please library(dtplyr)!\n",
      "------------------------------------------------------------------------------\n",
      "\n",
      "Attaching package: 'dplyr'\n",
      "\n",
      "The following objects are masked from 'package:data.table':\n",
      "\n",
      "    between, first, last\n",
      "\n",
      "The following objects are masked from 'package:stats':\n",
      "\n",
      "    filter, lag\n",
      "\n",
      "The following objects are masked from 'package:base':\n",
      "\n",
      "    intersect, setdiff, setequal, union\n",
      "\n"
     ]
    }
   ],
   "source": [
    "library(data.table)\n",
    "library(dplyr)\n",
    "library(ggplot2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Download the data\n",
    "download.file(url='http://dvn-vm1.hmdc.harvard.edu/data/mysql/irclog/irclog.tsv', destfile='data/irclog.tsv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df <- fread(\"data/irclog.tsv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.table: 3 × 8</caption>\n",
       "<thead>\n",
       "\t<tr><th scope=col>id</th><th scope=col>channel</th><th scope=col>day</th><th scope=col>nick</th><th scope=col>timestamp</th><th scope=col>line</th><th scope=col>spam</th><th scope=col>in_summary</th></tr>\n",
       "\t<tr><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><td>1</td><td>#dvn</td><td>2012-12-08</td><td>       </td><td>1355005146</td><td>iqlogbot joined #dvn                                                                                                                                                  </td><td>0</td><td>0</td></tr>\n",
       "\t<tr><td>2</td><td>#dvn</td><td>2012-12-08</td><td>       </td><td>1355005248</td><td>Topic for #dvn is now http://thedata.org - The Dataverse Network Project | logs at http://irclog.iq.harvard.edu/dvn/today                                             </td><td>0</td><td>0</td></tr>\n",
       "\t<tr><td>3</td><td>#dvn</td><td>2012-12-08</td><td>pdurbin</td><td>1355005351</td><td>hello! welcome to #dvn, an IRC channel on Freenode about The Dataverse Network Project, a web application for sharing, citing, analyzing, and preserving research data</td><td>0</td><td>0</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.table: 3 × 8\n",
       "\\begin{tabular}{r|llllllll}\n",
       " id & channel & day & nick & timestamp & line & spam & in\\_summary\\\\\n",
       " <int> & <chr> & <chr> & <chr> & <int> & <chr> & <int> & <int>\\\\\n",
       "\\hline\n",
       "\t 1 & \\#dvn & 2012-12-08 &         & 1355005146 & iqlogbot joined \\#dvn                                                                                                                                                   & 0 & 0\\\\\n",
       "\t 2 & \\#dvn & 2012-12-08 &         & 1355005248 & Topic for \\#dvn is now http://thedata.org - The Dataverse Network Project \\textbar{} logs at http://irclog.iq.harvard.edu/dvn/today                                              & 0 & 0\\\\\n",
       "\t 3 & \\#dvn & 2012-12-08 & pdurbin & 1355005351 & hello! welcome to \\#dvn, an IRC channel on Freenode about The Dataverse Network Project, a web application for sharing, citing, analyzing, and preserving research data & 0 & 0\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.table: 3 × 8\n",
       "\n",
       "| id &lt;int&gt; | channel &lt;chr&gt; | day &lt;chr&gt; | nick &lt;chr&gt; | timestamp &lt;int&gt; | line &lt;chr&gt; | spam &lt;int&gt; | in_summary &lt;int&gt; |\n",
       "|---|---|---|---|---|---|---|---|\n",
       "| 1 | #dvn | 2012-12-08 | <!----> | 1355005146 | iqlogbot joined #dvn                                                                                                                                                   | 0 | 0 |\n",
       "| 2 | #dvn | 2012-12-08 | <!----> | 1355005248 | Topic for #dvn is now http://thedata.org - The Dataverse Network Project | logs at http://irclog.iq.harvard.edu/dvn/today                                              | 0 | 0 |\n",
       "| 3 | #dvn | 2012-12-08 | pdurbin | 1355005351 | hello! welcome to #dvn, an IRC channel on Freenode about The Dataverse Network Project, a web application for sharing, citing, analyzing, and preserving research data | 0 | 0 |\n",
       "\n"
      ],
      "text/plain": [
       "  id channel day        nick    timestamp \n",
       "1 1  #dvn    2012-12-08         1355005146\n",
       "2 2  #dvn    2012-12-08         1355005248\n",
       "3 3  #dvn    2012-12-08 pdurbin 1355005351\n",
       "  line                                                                                                                                                                  \n",
       "1 iqlogbot joined #dvn                                                                                                                                                  \n",
       "2 Topic for #dvn is now http://thedata.org - The Dataverse Network Project | logs at http://irclog.iq.harvard.edu/dvn/today                                             \n",
       "3 hello! welcome to #dvn, an IRC channel on Freenode about The Dataverse Network Project, a web application for sharing, citing, analyzing, and preserving research data\n",
       "  spam in_summary\n",
       "1 0    0         \n",
       "2 0    0         \n",
       "3 0    0         "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "head(df,3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Make a new table which lists each nickname and the number of messages issued by that nickname\n",
    "chat.freq <- as.data.frame(table(df$nick))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Sort nicknames based on frequency\n",
    "chat.freq.sorted <- chat.freq[order(-chat.freq$Freq),]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 6 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>Var1</th><th scope=col>Freq</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>1</th><td>            </td><td>32987</td></tr>\n",
       "\t<tr><th scope=row>348</th><td>pdurbin     </td><td>26847</td></tr>\n",
       "\t<tr><th scope=row>338</th><td>pameyer     </td><td> 4859</td></tr>\n",
       "\t<tr><th scope=row>365</th><td>poikilotherm</td><td> 4454</td></tr>\n",
       "\t<tr><th scope=row>146</th><td>donsizemore </td><td> 3652</td></tr>\n",
       "\t<tr><th scope=row>68</th><td>bencomp     </td><td> 2753</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 6 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       "  & Var1 & Freq\\\\\n",
       "  & <fct> & <int>\\\\\n",
       "\\hline\n",
       "\t1 &              & 32987\\\\\n",
       "\t348 & pdurbin      & 26847\\\\\n",
       "\t338 & pameyer      &  4859\\\\\n",
       "\t365 & poikilotherm &  4454\\\\\n",
       "\t146 & donsizemore  &  3652\\\\\n",
       "\t68 & bencomp      &  2753\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 6 × 2\n",
       "\n",
       "| <!--/--> | Var1 &lt;fct&gt; | Freq &lt;int&gt; |\n",
       "|---|---|---|\n",
       "| 1 | <!----> | 32987 |\n",
       "| 348 | pdurbin      | 26847 |\n",
       "| 338 | pameyer      |  4859 |\n",
       "| 365 | poikilotherm |  4454 |\n",
       "| 146 | donsizemore  |  3652 |\n",
       "| 68 | bencomp      |  2753 |\n",
       "\n"
      ],
      "text/plain": [
       "    Var1         Freq \n",
       "1                32987\n",
       "348 pdurbin      26847\n",
       "338 pameyer       4859\n",
       "365 poikilotherm  4454\n",
       "146 donsizemore   3652\n",
       "68  bencomp       2753"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Notice the numerous entries associated with no nickname (Row 1).\n",
    "head(chat.freq.sorted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove any entries with blank nickname\n",
    "chat.freq.sorted <- chat.freq.sorted[chat.freq.sorted$Var1!=\"\",]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "#Filter out the top 25\n",
    "superusers <- chat.freq.sorted[1:25,]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Order the nickname levels based on frequency; this is the order the plot will show\n",
    "superusers$Var1 <- factor(superusers$Var1, levels = superusers$Var1[order(superusers$Freq)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Fetch and format min and max dates of the data\n",
    "date.min <- min(df$day) %>% as.Date() %>% format(format=\"%b %d, %Y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "date.max <- max(df$day) %>% as.Date() %>% format(format=\"%b %d, %Y\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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SVS3C/fae4tPYPM0E8o7q0fNNjXJlLQ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",
      "text/plain": [
       "plot without title"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot\n",
    "ggplot(superusers, aes(x=Var1, y=Freq, label=Freq)) +\n",
    "    geom_col() +\n",
    "    coord_flip() +\n",
    "    geom_text(size=3, hjust=\"bottom\") +\n",
    "    labs(title=\"Top Contributors in the Dataverse Chatroom\", subtitle=paste(\"From \", date.min, \" to \", date.max), x=\"User\", y=\"Total Messages\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "ggsave(\"ircsuperusers.png\", width = 6, height = 7)"
   ]
  },
  {
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      "text/html": [
       "<table>\n",
       "<caption>A data.frame: 25 × 2</caption>\n",
       "<thead>\n",
       "\t<tr><th></th><th scope=col>Var1</th><th scope=col>Freq</th></tr>\n",
       "\t<tr><th></th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
       "</thead>\n",
       "<tbody>\n",
       "\t<tr><th scope=row>348</th><td>pdurbin       </td><td>26847</td></tr>\n",
       "\t<tr><th scope=row>338</th><td>pameyer       </td><td> 4859</td></tr>\n",
       "\t<tr><th scope=row>365</th><td>poikilotherm  </td><td> 4454</td></tr>\n",
       "\t<tr><th scope=row>146</th><td>donsizemore   </td><td> 3652</td></tr>\n",
       "\t<tr><th scope=row>68</th><td>bencomp       </td><td> 2753</td></tr>\n",
       "\t<tr><th scope=row>77</th><td>bjonnh        </td><td> 1247</td></tr>\n",
       "\t<tr><th scope=row>51</th><td>andrewSC      </td><td> 1047</td></tr>\n",
       "\t<tr><th scope=row>425</th><td>skay          </td><td>  943</td></tr>\n",
       "\t<tr><th scope=row>384</th><td>romainM       </td><td>  888</td></tr>\n",
       "\t<tr><th scope=row>460</th><td>Thalia_UM     </td><td>  836</td></tr>\n",
       "\t<tr><th scope=row>99</th><td>cdsp-rmo      </td><td>  659</td></tr>\n",
       "\t<tr><th scope=row>124</th><td>dataverse-user</td><td>  520</td></tr>\n",
       "\t<tr><th scope=row>459</th><td>Thali_UM      </td><td>  500</td></tr>\n",
       "\t<tr><th scope=row>399</th><td>sbmarks       </td><td>  449</td></tr>\n",
       "\t<tr><th scope=row>22</th><td>* pdurbin     </td><td>  396</td></tr>\n",
       "\t<tr><th scope=row>267</th><td>jwhitney      </td><td>  356</td></tr>\n",
       "\t<tr><th scope=row>293</th><td>Mahsa         </td><td>  324</td></tr>\n",
       "\t<tr><th scope=row>62</th><td>axfelix       </td><td>  311</td></tr>\n",
       "\t<tr><th scope=row>317</th><td>michbarsinai  </td><td>  309</td></tr>\n",
       "\t<tr><th scope=row>349</th><td>pdurbin_m     </td><td>  304</td></tr>\n",
       "\t<tr><th scope=row>86</th><td>bricas        </td><td>  290</td></tr>\n",
       "\t<tr><th scope=row>380</th><td>rliebz        </td><td>  256</td></tr>\n",
       "\t<tr><th scope=row>325</th><td>MrK           </td><td>  245</td></tr>\n",
       "\t<tr><th scope=row>453</th><td>telnoratti    </td><td>  235</td></tr>\n",
       "\t<tr><th scope=row>442</th><td>soU           </td><td>  234</td></tr>\n",
       "</tbody>\n",
       "</table>\n"
      ],
      "text/latex": [
       "A data.frame: 25 × 2\n",
       "\\begin{tabular}{r|ll}\n",
       "  & Var1 & Freq\\\\\n",
       "  & <fct> & <int>\\\\\n",
       "\\hline\n",
       "\t348 & pdurbin        & 26847\\\\\n",
       "\t338 & pameyer        &  4859\\\\\n",
       "\t365 & poikilotherm   &  4454\\\\\n",
       "\t146 & donsizemore    &  3652\\\\\n",
       "\t68 & bencomp        &  2753\\\\\n",
       "\t77 & bjonnh         &  1247\\\\\n",
       "\t51 & andrewSC       &  1047\\\\\n",
       "\t425 & skay           &   943\\\\\n",
       "\t384 & romainM        &   888\\\\\n",
       "\t460 & Thalia\\_UM      &   836\\\\\n",
       "\t99 & cdsp-rmo       &   659\\\\\n",
       "\t124 & dataverse-user &   520\\\\\n",
       "\t459 & Thali\\_UM       &   500\\\\\n",
       "\t399 & sbmarks        &   449\\\\\n",
       "\t22 & * pdurbin      &   396\\\\\n",
       "\t267 & jwhitney       &   356\\\\\n",
       "\t293 & Mahsa          &   324\\\\\n",
       "\t62 & axfelix        &   311\\\\\n",
       "\t317 & michbarsinai   &   309\\\\\n",
       "\t349 & pdurbin\\_m      &   304\\\\\n",
       "\t86 & bricas         &   290\\\\\n",
       "\t380 & rliebz         &   256\\\\\n",
       "\t325 & MrK            &   245\\\\\n",
       "\t453 & telnoratti     &   235\\\\\n",
       "\t442 & soU            &   234\\\\\n",
       "\\end{tabular}\n"
      ],
      "text/markdown": [
       "\n",
       "A data.frame: 25 × 2\n",
       "\n",
       "| <!--/--> | Var1 &lt;fct&gt; | Freq &lt;int&gt; |\n",
       "|---|---|---|\n",
       "| 348 | pdurbin        | 26847 |\n",
       "| 338 | pameyer        |  4859 |\n",
       "| 365 | poikilotherm   |  4454 |\n",
       "| 146 | donsizemore    |  3652 |\n",
       "| 68 | bencomp        |  2753 |\n",
       "| 77 | bjonnh         |  1247 |\n",
       "| 51 | andrewSC       |  1047 |\n",
       "| 425 | skay           |   943 |\n",
       "| 384 | romainM        |   888 |\n",
       "| 460 | Thalia_UM      |   836 |\n",
       "| 99 | cdsp-rmo       |   659 |\n",
       "| 124 | dataverse-user |   520 |\n",
       "| 459 | Thali_UM       |   500 |\n",
       "| 399 | sbmarks        |   449 |\n",
       "| 22 | * pdurbin      |   396 |\n",
       "| 267 | jwhitney       |   356 |\n",
       "| 293 | Mahsa          |   324 |\n",
       "| 62 | axfelix        |   311 |\n",
       "| 317 | michbarsinai   |   309 |\n",
       "| 349 | pdurbin_m      |   304 |\n",
       "| 86 | bricas         |   290 |\n",
       "| 380 | rliebz         |   256 |\n",
       "| 325 | MrK            |   245 |\n",
       "| 453 | telnoratti     |   235 |\n",
       "| 442 | soU            |   234 |\n",
       "\n"
      ],
      "text/plain": [
       "    Var1           Freq \n",
       "348 pdurbin        26847\n",
       "338 pameyer         4859\n",
       "365 poikilotherm    4454\n",
       "146 donsizemore     3652\n",
       "68  bencomp         2753\n",
       "77  bjonnh          1247\n",
       "51  andrewSC        1047\n",
       "425 skay             943\n",
       "384 romainM          888\n",
       "460 Thalia_UM        836\n",
       "99  cdsp-rmo         659\n",
       "124 dataverse-user   520\n",
       "459 Thali_UM         500\n",
       "399 sbmarks          449\n",
       "22  * pdurbin        396\n",
       "267 jwhitney         356\n",
       "293 Mahsa            324\n",
       "62  axfelix          311\n",
       "317 michbarsinai     309\n",
       "349 pdurbin_m        304\n",
       "86  bricas           290\n",
       "380 rliebz           256\n",
       "325 MrK              245\n",
       "453 telnoratti       235\n",
       "442 soU              234"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "superusers"
   ]
  }
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