{
 "cells": [
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Analyzing the Social Networks of over 2.7 Billion Reddit Comments"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "This notebook gives detailed information to help better understand our paper. In this notebook, we will demonstrate how to construct the subreddits' social networks created by more than 2.7 billion comments. Additionally, we will demonstrate how to calculate various statistics related to the subreddits. This code is licensed under a BSD license. See [license file]()."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 0. Setup"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before we begin, make sure you have installed all the required Python packages. (The instructions below use pip. You can use easy_install, too.) Also, consider using virtualenv for a cleaner installation experience instead of sudo. We also recommend running the code via IPython Notebook.\n",
    "* sudo pip install --upgrade graphlab-create # We mainly used SFrame object, which is an open source package.\n",
    "* sudo pip install --upgrade praw\n",
    "* sudo pip install --upgrade seaborn\n",
    "* sudo pip install --upgrade networkx"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Preparing the Dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, we need to download the compressed Reddit dataset files from [pushshift.io website](http://files.pushshift.io/reddit/comments/). This dataset was created by [Jason Michael Baumgartner](https://twitter.com/jasonbaumgartne). Additional details about this dataset can be found at this [Link](https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/). Downloading this hundreds-of-GB dataset can take a considerable amount of time. To save time, you can download only one month’s, or several months’, worth of data. After we download the dataset, we notice that the dataset is organized in directories, where each directory contains the posts of a specific year. These directories contain posts that were published from December 2005 to the most recent month. For this tutorial, we utilized over 2.71 billion comments that were posted from December 2005 through October 2016. Let's create a single SFrame that contains all these posts. To achieve this, we first will convert each monthly zipped file into an SFrame object using the following code:"
   ]
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      "This non-commercial license of GraphLab Create for academic use is assigned .\n"
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     "name": "stdout",
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     "text": [
      "------------------------------------------------------\n",
      "Inferred types from first 100 line(s) of file as \n",
      "column_type_hints=[dict]\n",
      "If parsing fails due to incorrect types, you can correct\n",
      "the inferred type list above and pass it to read_csv in\n",
      "the column_type_hints argument\n",
      "------------------------------------------------------\n"
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     "name": "stdout",
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     "text": [
      "------------------------------------------------------\n",
      "Inferred types from first 100 line(s) of file as \n",
      "column_type_hints=[dict]\n",
      "If parsing fails due to incorrect types, you can correct\n",
      "the inferred type list above and pass it to read_csv in\n",
      "the column_type_hints argument\n",
      "------------------------------------------------------\n"
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   ],
   "source": [
    "import os\n",
    "import logging\n",
    "import bz2\n",
    "from datetime import datetime\n",
    "import graphlab as gl\n",
    "import graphlab.aggregate as agg\n",
    "import fnmatch\n",
    "\n",
    "gl.canvas.set_target('ipynb')\n",
    "gl.set_runtime_config('GRAPHLAB_CACHE_FILE_LOCATIONS', '/data/tmp')\n",
    "gl.set_runtime_config('GRAPHLAB_DEFAULT_NUM_GRAPH_LAMBDA_WORKERS', 128)\n",
    "gl.set_runtime_config('GRAPHLAB_DEFAULT_NUM_PYLAMBDA_WORKERS', 128)\n",
    "\n",
    "\n",
    "basedir = \"/data/reddit/raw\" # Replace this with the directory which you downloaded the file into\n",
    "sframes_dir = \"/data/reddit/sframes/\" # Replace this with the directory you want to save the SFrame to\n",
    "tmp_dir =  \"/data/tmp\" # Replace this with the directory you want to save the SFrame to\n",
    "\n",
    "def get_month_from_path(path):\n",
    "    m = os.path.basename(path)\n",
    "    m = m.split(\".\")[0]\n",
    "    return int(m.split(\"-\")[-1])\n",
    "\n",
    "def get_year_from_path(path):\n",
    "    y = os.path.basename(path)\n",
    "    y = y.split(\".\")[0]\n",
    "    return int(y.lower().replace(\"rc_\",\"\").split(\"-\")[0])\n",
    "\n",
    "def json2sframe(path):\n",
    "    \"\"\"\n",
    "    Creates an SFrame object from the file in the input path\n",
    "    :param path: path to a file that contains a list of JSON objects, each JSON is saved in a separate line.\n",
    "        The file can also be compressed in bz2 format.\n",
    "    :return: SFrame object created from the file in the input path. The SFrame also contains information regarding\n",
    "     each post date & time\n",
    "    :rtype: gl.SFrame\n",
    "    \"\"\"\n",
    "    if not path.endswith(\".bz2\"):\n",
    "        sf = gl.SFrame.read_json(path, orient=\"lines\")\n",
    "    else:\n",
    "        dpath = decompress_bz2(path)\n",
    "        sf = gl.SFrame.read_json(dpath, orient=\"lines\")\n",
    "        #remove the decompressed file\n",
    "        os.remove(dpath)\n",
    "    #add datetime information\n",
    "    sf['month'] = get_month_from_path(path)\n",
    "    sf['year'] = get_year_from_path(path)\n",
    "    sf['datetime']= sf[\"created_utc\"].apply(lambda utc: datetime.fromtimestamp(float(utc)))\n",
    "\n",
    "    return sf\n",
    "\n",
    "def decompress_bz2(inpath, outpath=None):\n",
    "    \"\"\"\n",
    "    Decompress bz2 to the outpath, if the outpath is not provided then decompress the file to the inpath directory\n",
    "    :param inpath: decompress bz2 file to the outpath\n",
    "    :param outpath: output path for the decompress file\n",
    "    :return: the output file path\n",
    "    \"\"\"\n",
    "    if outpath is None:\n",
    "        outpath = tmp_dir + os.path.sep + os.path.basename(inpath) + \".decompressed\"\n",
    "    out_file = file(outpath, 'wb')\n",
    "    logging.info(\"Decompressing file %s to %s\" % (inpath,outpath))\n",
    "    in_file = bz2.BZ2File(inpath, 'rb')\n",
    "    for data in iter(lambda : in_file.read(100 * 1024), b''):\n",
    "        out_file.write(data)\n",
    "    out_file.close()\n",
    "    in_file.close()\n",
    "    return outpath\n",
    "\n",
    "def match_files_in_dir(basedir, ext):\n",
    "    \"\"\"\n",
    "    Find all files in the basedir with 'ext' as filename extension\n",
    "    :param basedir: input basedir\n",
    "    :param ext: filename extension\n",
    "    :return: list of file paths with the input extension\n",
    "    \"\"\"\n",
    "    matches = []\n",
    "    for root, dirnames, filenames in os.walk(basedir):\n",
    "        for filename in fnmatch.filter(filenames, ext):\n",
    "            matches.append(os.path.join(root, filename))\n",
    "    return matches\n",
    "\n",
    "#Creating all SFrames\n",
    "for p in match_files_in_dir(basedir, \"*.bz2\"):\n",
    "    logging.info(\"Analyzing of %s \" % p)\n",
    "    outp = sframes_dir + os.path.sep + os.path.basename(p).replace(\".bz2\", \".sframe\")\n",
    "    if os.path.isdir(outp): #if file already exists skip it\n",
    "        logging.info(\"Skipping the analysis of %s file\" % p)\n",
    "        continue\n",
    "    sf = json2sframe(p)\n",
    "    sf.save(outp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let’s join all the SFrame objects into a single object. Please notice that different posts contain different metadata information about each post. Therefore, we will create a single SFrame which contains all the various metadata information."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "join_sframe_path = sframes_dir + os.path.sep + \"join_all.sframe\" # Where to save the join large SFrame object\n",
    "def get_all_cols_names(sframes_dir):\n",
    "    \"\"\"\n",
    "    Return the column names of all SFrames in the input path\n",
    "    :param sframes_dir: directory path which contains SFrames\n",
    "    :return: list of all the column names in all the sframes in the input directory\n",
    "    :rtype: set()\n",
    "    \"\"\"\n",
    "    sframes_paths = [sframes_dir + os.path.sep + s for s in  os.listdir(sframes_dir)]\n",
    "    column_names = set()\n",
    "    for p in sframes_paths:\n",
    "        if not p.endswith(\".sframe\"):\n",
    "            continue\n",
    "        print p\n",
    "        sf = gl.load_sframe(p)\n",
    "        column_names |= set(sf.column_names())\n",
    "    return column_names\n",
    "\n",
    "def get_sframe_columns_type_dict(sf):\n",
    "    \"\"\"\n",
    "    Returns a dict with the sframe column names as keys and column types as values\n",
    "    :param sf: input SFrame\n",
    "    :return: dict with the sframe column names as keys and column types as values\n",
    "    :rtype dict[str,str]\n",
    "    \"\"\"\n",
    "    n = sf.column_names()\n",
    "    t = sf.column_types()\n",
    "\n",
    "    return {n[i]: t[i]for i in range(len(n))}\n",
    "\n",
    "def update_sframe_columns_types(sf, col_types):\n",
    "    \"\"\"\n",
    "    Updates the input sframe column types according to the input types dict.\n",
    "    :param sf: input SFrame object\n",
    "    :param col_types: dict in which the keys are the column names and the values are the columns types\n",
    "    :return: SFrame object with column types update to the col_types dict. If a column doesn't exist in the SFrame object\n",
    "     then a new column is added with None values\n",
    "    :rtype: gl.SFrame\n",
    "    \"\"\"\n",
    "    sf_cols_dict = get_sframe_columns_type_dict(sf)\n",
    "\n",
    "    for k,v in col_types.iteritems():\n",
    "        if k not in sf_cols_dict:\n",
    "            sf[k] = None\n",
    "            sf[k] = sf[k].astype(v)\n",
    "        elif v != sf_cols_dict[k]:\n",
    "            sf[k] = sf[k].astype(v)\n",
    "    return sf\n",
    "\n",
    "def join_all_sframes(sframes_dir, col_types):\n",
    "    \"\"\"\n",
    "    Joins all SFrames in the input directory where the column types are according to col_types dict\n",
    "    :param sframes_dir:\n",
    "    :param col_types: dict with column names and their corresponding types\n",
    "    :return: merged SFrame of all the SFrames in the input directory\n",
    "    \"rtype: gl.SFrame\n",
    "    \"\"\"\n",
    "    sframes_paths = [sframes_dir + os.path.sep + s for s in  os.listdir(sframes_dir) if s.endswith(\".sframe\")]\n",
    "    sframes_paths.sort()\n",
    "    sf = gl.load_sframe(sframes_paths[0])\n",
    "    sf = update_sframe_columns_types(sf, col_types)\n",
    "    for p in sframes_paths[1:]:\n",
    "        if not p.endswith(\".sframe\"):\n",
    "            continue\n",
    "        print \"Joining %s\" % p\n",
    "        sf2 = update_sframe_columns_types(gl.load_sframe(p), col_types)\n",
    "        sf2.__materialize__()\n",
    "        sf = sf.append(sf2)\n",
    "        sf.__materialize__()\n",
    "\n",
    "    return sf\n",
    "\n",
    "\n",
    "\n",
    "# use the inferred column type according to last month posts' SFrame. Set all other columns to be \n",
    "# as type str\n",
    "#col_names = get_all_cols_names(sframes_dir)\n",
    "sf = gl.load_sframe(sframes_dir + '/RC_2015-05.sframe')\n",
    "d = get_sframe_columns_type_dict(sf)\n",
    "for c in col_names:\n",
    "    if c not in d:\n",
    "        print \"Found new column %s\" %c\n",
    "    d[c] = str\n",
    "\n",
    "#Create Single SFrame\n",
    "sf = join_all_sframes(sframes_dir, d)\n",
    "sf.save(join_sframe_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At the end of this process, we obtained an SFrame with 2,718,784,464 rows, which is about 444 GB in size. Let's use the show function to get a better understanding of the data.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "gl.canvas.set_target('ipynb')\n",
    "sf = gl.load_sframe(join_sframe_path)\n",
    "#sf.show() # running this can take considerable amount of time"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's clean it by removing columns that aren't useful for creating the subreddit's social network. Namely, we remove the following columns: \"archived,\" \"downs,\" \"retrieved_on,\" \"banned_by,\" \"likes,\" \"user_reports,\" \"saved,\" \"report_reasons,\" \"approved_by,\" \"body_html,\" \"created,\" \"mod_reports,\" and \"num_reports.”\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "sf = sf.remove_columns([\"archived\", \"downs\", \"retrieved_on\", \"banned_by\", \"likes\",\"user_reports\", \"saved\",\n",
    "                        \"report_reasons\", \"approved_by\", \"body_html\", \"created\", \"mod_reports\", \"num_reports\"])\n",
    "sf.__materialize__()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's also delete users' posts that are from users that are probably bots and from those who have posted too many messages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+-----------+\n",
      "|        author        |   Count   |\n",
      "+----------------------+-----------+\n",
      "|      [deleted]       | 302138049 |\n",
      "|    AutoModerator     |  10976942 |\n",
      "|     conspirobot      |   575576  |\n",
      "|    ModerationLog     |   562192  |\n",
      "|     TweetPoster      |   555976  |\n",
      "|    MTGCardFetcher    |   444411  |\n",
      "|        RPBot         |   436199  |\n",
      "|     autowikibot      |   422769  |\n",
      "|   imgurtranscriber   |   404441  |\n",
      "|      PoliticBot      |   388444  |\n",
      "|      dogetipbot      |   374536  |\n",
      "|   ImagesOfNetwork    |   355037  |\n",
      "| throwthrowawaytothee |   344583  |\n",
      "| Late_Night_Grumbler  |   320383  |\n",
      "|   qkme_transcriber   |   301974  |\n",
      "| TweetsInCommentsBot  |   282467  |\n",
      "|    TotesMessenger    |   222073  |\n",
      "|     Franciscouzo     |   202346  |\n",
      "|      havoc_bot       |   197761  |\n",
      "|     morbiusgreen     |   195312  |\n",
      "|    User_Simulator    |   194358  |\n",
      "|        Lots42        |   192985  |\n",
      "|       hit_bot        |   182189  |\n",
      "|         -rix         |   173022  |\n",
      "|      pixis-4950      |   171907  |\n",
      "|     PornOverlord     |   171623  |\n",
      "|    BitcoinAllBot     |   170096  |\n",
      "|     UnluckyLuke      |   169971  |\n",
      "|     PriceZombie      |   163710  |\n",
      "|      amici_ursi      |   163288  |\n",
      "|        matts2        |   156381  |\n",
      "|       gifv-bot       |   155513  |\n",
      "| WritingPromptsRobot  |   154295  |\n",
      "|    atomicimploder    |   148904  |\n",
      "|       autotldr       |   146046  |\n",
      "|      TrollaBot       |   145737  |\n",
      "|     SnapshillBot     |   143317  |\n",
      "|   NoMoreNicksLeft    |   135738  |\n",
      "|      MovieGuide      |   134567  |\n",
      "|      raddit-bot      |   133615  |\n",
      "|       iam4real       |   133262  |\n",
      "|   youtubefactsbot    |   132521  |\n",
      "|      CaptionBot      |   131743  |\n",
      "|        hwsbot        |   131402  |\n",
      "|       G_Morgan       |   129057  |\n",
      "|      davidjl123      |   128481  |\n",
      "|     noeatnosleep     |   125357  |\n",
      "|     samacharbot2     |   125226  |\n",
      "|    backpackwayne     |   116002  |\n",
      "|     ttumblrbots      |   114590  |\n",
      "+----------------------+-----------+\n",
      "[20299812 rows x 2 columns]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "#First let's find how many posts the most active users posted\n",
    "posts_count_sf = sf.groupby('author', gl.aggregate.COUNT())\n",
    "posts_count_sf.sort('Count',ascending=False).print_rows(50)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To clean the dataset, we removed redditors who posted over 100,000 times and seemed to post automatic content. Additionally, we used the [praw Python package](https://praw.readthedocs.io/en/latest/) to parse the comments posted in the [BotWatchman subreddit](https://www.reddit.com/r/BotWatchman/) in order to identify bots and remove them. We use the following code to assemble a bots list:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Delete Users List (951 users):\n",
      " set(['Removedpixel', 'SoulFire6464', u'RealtechPostBot', u'serendipitybot', u'r2d8', u'arethemodsasleep', u'squis1000', u'The_Penis_Game_Bot', u'whooshbot', u'Zyra_test', u'hitlerbotv2', u'topredditbot', u'VerseBot', u'MusicB0t', u'Explains_FTFY', u'BaddieBot', u'autourbanbot', 'NinjaDiscoJesus', u'thier_2_their_bot', u'amProbablyPooping', u'Insane_Photo_Bot', u'Auto_Neckbeard_Bot', u'shadowbanbot', u'_Rita_', u'Profanity-bot', u'gracefulclaritybot', u'DataFire_bot', 'autowikibot', u'FTFY_Cat', u'yes_answers.', u'DollarSignDouche', u'ELIMINATE_GIFS', u'PlusOneBot', u'CutoutBot', u'visual_clarification', u'triggeredbot', u'haiku_finder_bot', u'Eats_Small_Text_Bot', u'GameDealsBot', u'Craigslist-Bot', u'STEALTHM0UNTAIN', u'LegoLinkBot', 'atomicimploder', u'Dickish_Bot_Bot', 'BitcoinAllBot', u'/u/codes_comments', u'CuteBot6969', u'LittleHelperRobot', u'Anti-Brigade-Bot3', u'autowikiabot', u'Anti-Brigade-Bot8', 'backpackwayne', u'UnobtaniumTipBot', u'YOGSbot', u'Innocence_bot2', u'PreserverBot', u'givesafuckbot', u'youreyoureiswrong', u'gabenizer-bot', u'crushe69', u'Canadian-Sorry-Bot', u'Comrade__Bot', u'GunnitBot', u'checks_for_checks', u'define_bot', u'Hikelsa_bot', u'ThanksObamaBiden', u'rusetipbot', 'pixis-4950', u'autotrope_bot', u'Feathersbumbled', u'NSLbot', u'kittehcointipbot', u'ModisDead', u'ItsSpelledPrincipal', u'demobile_bot', u'acini', u'rawlaying90', u'OneBleachinBot', u'giddyp93', u'NobodyDoesThis', u'image_linker_bot', u'ReddiTron1000', u'WWE_Network_Bot', u'iTunesLinks', u'TheWallGrows', u'PokemonFlairBot', u'StockTrendsBot', u'pikachu_hsu', u'PM_ME_YOUR_COCK_', 'CaptionBot', u'FucksWithTables', u'The_Dad_Bot', u'hearing-aid_bot', u'bee2kg', u'IPostAlotBot', u'stockinfo_bot', u'ASOT_Tracklister_bot', u'resavr_bot', u'chant89', u'StackBot', u'it-is-not-would-of', u'Converts2Useless', u'OnlyRepliesLMAO', u'WillPrismWordsBot', u'magic-8-bot', '-rix', u'DUCCI__BOT', u'Product_Helper_Bot', u'CationBot', u'Readdit_Bot', u'shiftace-', u'Comment_Codebreaker', u'ToBeFairBot', u'thank_mr_skeltal_bot', u'steam_bot', u'RFootballBot', u'ratsb1000', u'RedVanguardBot', u'AVR_Modbot', u'nulli1000', u'DidSomeoneSayBoobs', u'compilebot', u'Brigade_Bot', u'/u/TotesHuman', u'league_match_bot', u'_Sweetiebot', u'much-wow-doge', u'UselessAndBot', u'disapprovalbot', u'ButWhatDoIDoWithIt', u'ASCIICockBot', u'tabledresser', u'cruise_bot', 'G_Morgan', 'autotldr', 'PornOverlord', u'topcoin_tip', u'tagstr1000', u'heads_need_bodies', 'PoliticBot', u'bedoot', u'AAbot', u'gandhiwatchesbot', u'AladeenBot', u'iscuck_bot', u'nice_meme_bot', 'samacharbot2', u'dotaherobot', u'TreeFiddyBot', u'RedditAnalysisBot', u'b6d27f0x3', u'roger_bot', u'BotOfOriginality', u'TheTopCommentBot', u'annoying_yes_bot', u'isDegenerate', u'NightMirrorMoon', u'BOTFORSUBREDDITNAME', u'gandhi_spell_bot', u'Decronym', u'WikiBotEU', u'cartri69', u'ProfanityWatch', u'livid_taco', u'loser_detector_bot', u'IthkuilRobot', u'zalgoskeletor', u'PlayStoreLinks_Bot', u'ShillForMonsanto', u'BrokenArmsBot', u'qznc_bot', 'matts2', u'PonyTipBot', u'Twitch2YouTube', u'GabenCoinTipBot', u'gabentipbot', u'DogeLotteryModBot', u'DrivePower', u'alot-of-bot', u'The-Paranoid-Android', u'YouTube_Time', u'companymi69', u'NotApostolate', u'FFBot', u'wheres_the_karma_bot', u'Wolfram_Bot', u'ImageRehoster', u'highlightsbot', u'codex561', u'garu323', 'raddit-bot', u'YT_Timestamp_Bot', u'WeAppreciateYou', u'hhhehehe_BOT', u'skitchbot', 'Late_Night_Grumbler', u'MumeBot', u'not-cleverbot', u'Gestabot', 'NoMoreNicksLeft', u'TheSpellingAsshole', u'QuoteMe-Bot', u'Dad_Jokes_Inbound', u'lolpenisbot', u'you_thejoke', u'TerperBot', 'GoTradeBot', u'Nepene', u'greeter_bot', u'TitsOrGTFO_Bot', u'saskaai', u'ArmFixerBot', u'I_Love_You_Too_Bot', u'grreviews_bot', 'qkme_transcriber', u'ASOIAFSearchBot', u'Dad_Jokes_Incoming', u'Peteusse', 'SnapshillBot', u'Honey189', u'_AyyLmaoBot_', u'SoThereYouHaveIt', u'ferrarispider52', u'publicmodlogs', u'Joasdisle', u'ItWillGetBetterBot', u'thelinkfixerbot', u'CalvinBot', u'splin69', u'Anti-Brigade-Bot7', u'Rule_13_Bot', u'Shlak2k15', u'Handy_Related_Sub', u'BELITipBot', u'scraptip', u'Antiracism_Bot', u'auto-doge', u'PuushToImgurBot', '[deleted]', u'anusBot', u'Reddit2Trend', u'ToBeFairCounter', u'JotBot', u'WikipediaLinkFixer', u'NFLVideoBot', u'UrbanDicBot', u'maybemaybemaybe_bot', u'fieldpain6969', u'MaveTipBot', u'nsfw_gfys_bot2', u'CortanaBot', u'rumblep666', u'SmallTextReader', u'KSPortBot', u'Define_It', u'_TonyWonder_', u'wrapt6969', u'PnSProtectionService', 'throwthrowawaytothee', u'Control_F', u'XPostLinker', u'phrase_bot', u'TOP_COMMENT_OF_YORE', u'smile_today_', u'bitcointip', u'templatebot', u'Dictionary__Bot', u'Downtotes_Plz', u'Mr_Vladimir_Putin', u'gracefulcharitybot', u'A_random_gif', u'trpbot', u'MetricPleaseBot', u'redditShitBots', u'Anti-Brigade-Bot-35', u'MatchThreadder', u'GrammarianBot', u'SpellingB', u'Mobile_Version', u'Metric_System_Bot', u'FriendlyCamelCaseBot', u'I_Am_Genesis', 'TweetsInCommentsBot', u'AutoNiggaBot', u'DadBot3000', u'VideopokerBot', u'InformativeButFalse', u'mcservers-bot', u'sendto', u'classhole_bot', u'DNotesTip', u'TheAssBot', u'UselessArithmeticBot', u'GoogleTranslateBot', u'MAGNIFIER_BOT', u'DealWithItbot', u'NintendoVideoBot', u'CONFUSED_COPYCAT', u'Sandstorm_Bot', 'ttumblrbots', u'classybot', u'bitofnewsbot', u'MetatasticBot', u'post_only_cocks', u'Deviantart-Mirror', u'ImprovedGrammarBot', u'ShillHill666', u'EscapistVideoBot', u'AntiBrigadeBot', u'IRCR_Info_Bot', u'swiftwee88', u'ICouldntCareLessBot', u'X_BOT', u'clay_davis_bot', u'rumbl1000', u'My_Bot', u'panderingwhore', u'GeekWhackBot', u'TryShouldHaveInstead', u'SauceHunt', u'bust1nbot', u'valkyribot', u'WordCloudBot2', u'OnlyPostsJFC', u'wooshbot', u'infiltration_bot', 'PriceZombie', u'ContentForager', u'SatoshiTipBot', u'BoobBot3000', u'TheButtonStatsBot', u'MonsterMashBot', u'subtext-bot', u'shirley_bot', u'flower_bot', u'BensonTheBot', u'SwearWordPolice', u'Reddit_JS_Bot', u'corgicointip', u'SuchModBot', u'RAOM_Bot', u'haha_bot', u'WeatherReportBot', u'xkcd37bot', u'_chao_', u'NASCARThreadBot', u'/u/TARDIS-BOT', 'AutoModerator', u'ThePoliceBot', u'coinflipbot', u'spinnelein', u'meme_transcriber', 'rollme', u'TablesWillBeFlipped', u'anagrammm', u'rarchives', u'Anti-Brigade-Bot', u'pm_me_your_bw_pics', u'last_cakeday_bot', u'SRS_History_Bot', u'Nazeem_Bot', u'murde1', u'I_Say_No_', u'navigatorbot', u'Anti-Brigade-Bot-1', 'Lots42', u'ThePictureDescribot', u'VeteransResourcesBot', u'fact_check_bot', u'milestone_upvotes', u'goodnotesbot', u'hybrid377', u'BogdanGhita', u'RaceReporter', u'gives_you_boobies', u'Anti-Brigade-Bot-5', u'yes-bot.', u'SubredditMetadataBot', u'AutoInsult', u'mvinfo', u'coinyetipper', u'clothinf89', u'only_posts_chickens', u'Meta_Bot', 'WritingPromptsRobot', u'dgctipbot', u'Correct_Apostrophe_S', u'IAMARacistBot', u'_FallacyBot_', u'decidebot', u'HCE_Replacement_Bot', u'kitabi_vig', u'GrammarCorrectingBot', u'VideoLinkBot', u'scanr', u'GoogleForYouBot', u'Anti-brigade-bot-19', u'Team60sBot', u'Anything_At_All_', u'luckoftheshibe', u'forehead92', u'faketipbot', u'NotRedditEnough', u'FapFindr', u'WatchGroupBot', u'AbixBot', u'AyyLmao2DongerBot', u'thisbotsays', u'PhoenixBot', u'sentimentviewbot', u'AntiHateBrigadingBot', u'edward_r_servo', u'Le_xD_Bot', u'frontbot', u'bRMT_Bot', u'PunknRollBot', u'ConvertsToMetric', u'PCMasterRacebot', u'nba_gif_bot', u'yourebot', u'Could_Care_Corrector', u'GrammerNazi_', u'rubycointipbot', u'/u/hearingaid_bot', u'facts_sphere', 'TweetPoster', u'curly1232', u'AstrosBot', u'chromabot', u'LocationBot', u'webpage_down_bot', u'TheChosenBot', u'c5bot', u'subredditChecker', u'flips_title', u'ObamaRobot', u'ButtTipBot', 'User_Simulator', u'battery_bot', u'/r/bot_police', u'totes_alpha_bot', u'frytipbot', u'provides-id', u'RaGodOfTheSunisaCunt', u'TrendingBot', u'EDC_automod', u'Daily_Fail_Bot', u'lilliecute', u'slapbot', u'BASICALLY_LITERALLY', u'AntiBrigadeBot2', u'tmobaird', u'Link_Demobilizer', u'Spaghetti_Robotti', u'TalkieToasterBot', u'AllahuAkbarBot', u'LinkFixerBot1', u'LinkFixerBot2', u'LinkFixerBot3', 'hit_bot', u'math_or_math_joke', u'nbtip', u'howstat', u'Relevant_News_Bot', u'flip_text_bot', u'PresidentObama___', u'giftoslideshowdotcom', u'DownvotesMcGoats', u'malen-shutup-bot', u'Some_Bot', u'approve_unmoderated', u'leveretb89', u'Gukga-anjeon-bowibu', u'swearjar_bot', u'TheHandOfOmega', u'test_bot0x00', u'URLfixerBot', u'HowIsThisBestOf_Bot', u'RonaldTheRight', u'-faggotbot', u'colorcodebot', 'Franciscouzo', u'Somalia_Bot', 'youtubefactsbot', u'NSA_for_ELS', u'bosk_tino', u'reallygoodbot', u'no_context_bot', u'NoseyPantyBot', u'Shiny-Bot', u'RemindMeBotBro', u'inside_voices', u'penguingun', u'XboxDVRBot', u'GotCrypto', u'CAH_BLACK_BOT', u'ExpectedFactorialBot', u'vertcoinbot', u'NoSobStoryBot2', u'Smile_Bot', u'IFlipCoins', u'memedad-transcriber', u'I_Like_Spaghetti', u'PleaseRespectTables', u'xkcd_transcriber', u'CockBotHDEdition', u'golferbot', u'RemindMeBot', u'tyo-translate', u'GrasiaABot', u'JiffierBot', u'JumpToBot', u'new_eden_news_bot', u'CasualMetricBot', u'Unhandy_Related_Sub', u'tipmoonbot2', u'SwitcharooInventory', u'okc_rating_bot', u'RfreebandzBOT', u'BailyBot', u'MassdropBot', 'RPBot', u'Rad_Rad_Robot', u'pandatips', u'imgur_rehosting', u'YesManBot', u'CantHearYouBotEX', u'UselessConversionBot', u'MY_GLASSES_BITCH', u'Key_Points', u'AwkwardMod', u'JiffyBot', u'FunCatFacts', u'spursgifs_xposterbot', u'SRD_Notifier', 'noeatnosleep', u'isreactionary_bot', u'Sammy-SlimBot', u'PlaylisterBot', u'rotoreuters', u'Celeb_Username_Bot', u'digitipbot', u'reddtipbot', u'ImCongratulating', u'PM_UR_NUDES-PLEASE', u'PlayStoreLinks__Bot', u'HMF_Bot', u'DotaCastingBot', u'thankyoubot', u'A858DE45F56D9BC9', u'quack_bot', u'JennyCherry18', u'ShadowBannedBot', u'Mentioned_Videos', u'fedora_tip_bot', u'Captn_Hook', u'TDTMBot', u'/u/Wraptram', u'haikub0t', u'sunhatd1000', u'NewAustrian', u'Accountabili_bot', u'ExmoBot', u'isReactionaryBot', 'nikorasu_the_great', u'picsonlybot', u'shadowman735', u'jerkbot-3hunna', u'I_Dislike_Spaghetti', u'rss_feed', 'TotesMessenger', u'AutoCorrectionBot', u'LinkDemobilizerBot', u'MemeExDe', u'TicTacToeBot', u'SubredditLinkBot', u'the__meep', u'GoldFact', u'SERIAL_JOKE_KILLER', u'gender_bot', u'peekerbot', u'YTDLBot', u'CamptownRobot', u'_perly_bot', u'tagstra93', u'Barrack_Obama__', u'MuhOutrage_Bot', 'Sir_Willis_CMS', u'cake_day_bot', u'sports_gif_bot', u'StopSayingRIPinPBot', u'nyantip', u'Finnbot', u'Link_Correction_Bot', u'That_Attitude_Bot', u'AwkwardDev', 'dogetipbot', u'YouGotGlitched', u'MarkovBot', u'magic_8_bot', u'haiku_robot', u'AlaTull', u'DeltaBot', u'malo_the_bot', u'DEAL_WITH_IT_bot', 'eaturbrainz', u'Tereshang', u'OfficialCommentRater', u'WontRemindYou', u'BeHappyBot', u'lollygag1000', u'FTFYouBot', u'cahbot', u'CouldBeWorseBot', u'totes_meta_bot', u'autoleprabot', u'AsciBoobsBot', u'freeEBOOKS-Batman', u'WordcloudYou', 'davidjl123', u'English_Helper_Bot', u'I_BITCOIN_CATS', 'morbiusgreen', u'mirror__bot', u'asmccc4123', u'MontrealBot', u'metoobot', u'ac_502002', 'andrewsmith1986', u'citation-is-needed', u'SEO_Killer', u'vertcointipbot', u'VsauceBot', u'Mattyso', u'makeswordcloudsagain', u'The_Marco_Rubio', u'SWTOR_Helper_Bot', u'Virnibot', u'pi_day_bot', u'classhole_robot', u'Shrugfacebot', u'elMatadero_bot', u'Random-ComplimentBOT', u'GoneWildResearcher', u'AndMarquez', u'matthewrobo', u'EveryThingIsSoRaven', u'GreasyBacon', u'bajneeds', u'CantHearYouBot', u'stockbot2000', u'gfycat-bot-sucksdick', u'neutlime', u'let_me_nig_that_4_u', u'Polite_Users_Bot', u'captainhindsightbot', u'AgentKoenigLMD', u'Text_Reader_Bot', u'FedoraTipAutoBot', u'/u/BadSarcasmDetector', u'lmaoRobot', u'ban_pruner', u'elwh392', u'GandhiSpellingBot', u'TwitchToYoutubeBot', u'icehock6969', u'ddlbot', u'relevantxkcd-bot', u'RequirementsBot', u'h0b0_monkey', u'ImJimmieJohnsonBot', u'nrl_cfb', u'PaidBot', u'bitcoinpartybot', u'moderator-bot', u'baseball_gif_bot', u'DropBox_Bot', u'DownvotedComments', u'slickwom-bot', u'kuilinbot', u'Gatherer_bot', u'VideoPostBot', u'WPBot', u'DirectImageLinkerBot', u'user/no_context_bot.', u'jaysbot2', u'ShittyGandhiQuotes', u'stairs1000', u'Wiki_FirstPara_bot', u'Fixes_GrammerNazi_', u'HauntedHashbrown', u'FrownUpsideDownBot', u'Anti-Brigade-Bot-11', u'Anti-Brigade-Bot-12', u'kg2bee', u'RoundUp_bot', u'cmhocbot', u'imirror_bot', u'BHObamanator', u'JokingLikeaBot', u'InternetLyingPolice', u'Raptor_Reading', u'JeopardyQBot', u'PedanticIrishBot', u'domoarigatobtfcboto', u'BritishHaikuBot', u'SurviAvi', u'WikipediaPoster', 'ModerationLog', u'pandatipbot', u'foreigneducationbot', u'non_dm_mirror_bot', u'fedoratips', u'Anti-Reactionary-Bot', u'TheLazyLinker', u'CouldCareFewer', u'InceptionBwongBot', u'/u/trollmaster-5000', u'maaz7', u'allinonebot', u'LineBreakBot', u'WhoopThereItWas', u'u/alot-of-bot', u'AlbumHelperBot', u'NoSleepAutoMod', u'Your_Post_As_A_Movie', u'rSGSpolice', u'TipMoonBot', u'GivesSilverBot300', 'MovieGuide', 'TrollaBot', u'JakeandAmirBot', u'BlackjackBot', u'CHART_BOT', u'bandage1000', u'KarmaConspiracy_Bot', u'BigLebowskiBot', u'grumblehi88', u'BuildAPC4MeBot', u'BotAntagonist', u'clevercommen', u'unitconvert', u'dragoneno6969', u'CreepierSmileBot', u'CIRCLJERK_REPOST_BOT', u'Grumbler_bot', u'DetailsMaster', u'cageypro666', u'SakuraiBot', u'openseadragonizer', u'ImproperGrammarBot', 'imgurtranscriber', 'MasterT231', u'obamabot9000', u'zunjae', u'PoliteUsersBotBot', u'translatesit43times', u'Insigible_Bot', u'VoterBot', u'sara_son19', u'CarterDugSubLinkBot', u'Nidalee_Bot', u'ProductHelperBot', u'CantHearYouBot2', u'moanrigid90', u'changetip', u'redditbots', u'ApiContraption', 'smacksaw', u'RedditMarkovBot', u'edhrec', u'Ladonnalder', u'RepeatBOT', u'dirtymindrebel', u'YT_Bot', u'xkcd_number_bot', u'hitlerbot', u'Rangers_Bot', u'SexSellsStats', u'Forgotten_News_Bot', u'HFY_Tag_Bot', u'ARandomTipAppears', u'LinkedCommentBot', u'LEGO_not_LEGOS_', u'PopcornBot', u'FelineFacts', u'request_bot', u'ReadSmallTextBot', u'MirrorNinjaBot', u'CAH_TEST_BOT', u'delaybot', u'-ecksdee-', u'timewaitsforsome', u'grumpybot', 'MTGCardFetcher', u'BreakfastCerealBot', u'DailMail_Bot', u'tara1', u'SMCTipBot', u'gocougs_bot', u'ThenThanMistakeNoted', u'keysteal_bot', u'DJ_Khaled_Best', u'anon_bot', 'UnluckyLuke', u'beecointipbot', u'QuoteMeBot', u'videos_mod', u'Tumblr_In_Starbucks', u'ExplainsRemovals', u'ComplimentingBot', u'Videos_Mentioned', u'User_History_Bot', u'__bot__', u'Anti_Vladimir_Putin', u'connipti92', u'amazedbot', u'replieswithsmokeweed', u'CreepySmileBotFanBot', u'rule_bot', u'sunhatda666', u'StarboundBot', u'saysjokes', u'IQuoteYouBot', u'colombia_bot', u'zigzagh90', u'IAgreeBot', u'Codebreakerbreaker', u'auto_help_bot', u'PrettyMuchPrettyMuch', u'ADHDbot', u'so_doge_tip', u'ConvertsToText', u'PoliteBot', u'bocketybot', u'maddie_bot', 'ImagesOfNetwork', u'stats-bot', u'imgurerbot', u'potdealer', 'gifv-bot', u'f1bet', u'stormske91', u'notoverticalvideo', u'imgurHostBot', u'amumu_bot', u'Meta_Bot2', u'flappytip', u'Anti-Brigade-Bot-2', u'Anti-Brigade-Bot-3', u'ToMetric', u'Anti-Brigade-Bot-6', u'asmrspambot', u'recursion_bot', u'thewutbot', u'QUICHE-BOT', u'grammar_nazi_bot_13', u'GimliBot', u'AtheismModBot', u'Lionelttson', u'unsta666', u'friendlygame', u'testbotjen', u'sumthenews', u'calcolatore', u'CussWordPolice', u'FixYourGrammarBot', u'Reads_Small_Text_Bot', u'DRKTipBot', u'chawalbanda33', u'ProselytizerBot', u'MultiFunctionBot', u'historymodbot', u'Makes_Small_Text_Bot', u'untouchedURL', 'iam4real', u'LazyLinkerBot', u'tennis_gif_bot', u'Cakeday-Bot', u'IsItDownBot', u'NoGrasiaABot', u'WhenisHL3', u'Gynocologist_Bot', 'havoc_bot', u'archlinkbot', u'rbutrBot', u'DirectImageLinkBot', u'Birthdaytits', u'fa_mirror', u'New_Small_Text_Bot', u'Top_Comment_Repo_Man', 'conspirobot', u'cris9696', u'siteswap-bot', u'SketchNotSkit', u'Anti-Brigade-Bot1917', u'OriginalLinkBot', u'TitleLinkerBot', u'BensonTheSecond', u'godwin_finder', u'SmallSubBot', u'whispen', u'Shrug_Bot', u'raiseyourdongersbot', u'hearing_aids_bot', u'upmo', u'IS_IT_SOLVED', u'AltCodeBot', u'Wink-Bot', u'random-imgur', 'hwsbot', u'snapshot_bot', u'replies_randomly', 'TheNitromeFan', u'khalifa111', u'GoodGuyGold', u'FrontpageWatch', u'RelevantSummary', u'redditreviewbot', u'liver1000', u'Shakespeares_Ghost', u'gfy_bot', u'FirstThingsFirst_bot', u'Stop_Insulting_Mommy', u'a_lot_vs_alot_bot', 'amici_ursi', u'L-O-S-E_not_LOOSE', u'ComradeBot_', u'myrtipbot', u'expired_link_bot', u'Translates10Times', u'BeetusBot', u'ExplanationBot', u'HelperBot_', u'comment_copier_bot', u'Shinybot', u'Bronze-Bot', u'poonta93', u'Brybot', u'SmartphonePitchforks', u'ThatsWhatSheSaidAI', u'adverb_bot', u'RelatedBot', u'youtube_unblock_bot', u'CreepySmileBot', u'rightsbot', u'fsctipbot', u'ParenthesisBot', u'IM_DEFINITELY_A_BOT', u'Clickbait_ReplierBot'])\n"
     ]
    }
   ],
   "source": [
    "import praw\n",
    "\n",
    "\n",
    "def get_bots_set():\n",
    "    #Please insert your Reddit application's authentication information.\n",
    "    #See more details at: https://github.com/reddit/reddit/wiki/OAuth2-Quick-Start-Example#first-steps\n",
    "    secret ='<insert your secert string>'\n",
    "    client_id = '<insert your client-id string>'\n",
    "    user_agent = '<insert your user-agent string>'\n",
    "    \n",
    "    reddit = praw.Reddit(client_id=client_id,client_secret=secret, user_agent=user_agent)\n",
    "    sr = reddit.subreddit('BotWatchman')\n",
    "    bots_set = set()\n",
    "    for p in sr.search(\"overview for\", limit=2000):\n",
    "        bots_set.add(p.title.split(\" \")[2])\n",
    "    return bots_set    \n",
    "\n",
    "\n",
    "def get_remove_profiles_list(sf):\n",
    "    # We get the bots set twice to reduce the variance of the results\n",
    "    bots_set = get_bots_set()\n",
    "    bots_set |= get_bots_set()\n",
    "    posts_count_sf = sf.groupby('author', gl.aggregate.COUNT())\n",
    "    delete_users = set(posts_count_sf[posts_count_sf['Count'] > 100000]['author'])\n",
    "    delete_users |= bots_set\n",
    "    return delete_users\n",
    "\n",
    "\n",
    "delete_users = get_remove_profiles_list(sf)\n",
    "print \"Delete Users List (%s users):\\n %s\" % (len(delete_users), delete_users)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we used the following code to filter out comments posted by bot redditors that appeared in the bots list.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2389764512"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sf = sf[sf['author'].apply(lambda a: a not in delete_authors)]\n",
    "len(sf)\n",
    "sf.save(\"/data/reddit_data_no_txt_without_bots_and_deleted_authors.sframe\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are left with about 2.39 billion comments."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2. Analyzing Subreddits"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to better understand the structure and evolution of subreddits. Let's calculate some interesting statistics on these subreddit communities. We will start by calculating the number of unique subreddits, and then we’ll create histograms of the number of posts on each subreddit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The dataset contains 371833 unique subreddits.\n"
     ]
    }
   ],
   "source": [
    "#For running this section please make sure you created 'reddit_data_no_txt_without_bots_and_deleted_authors.sframe' as explained\n",
    "# in the previous section\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import graphlab as gl\n",
    "import graphlab.aggregate as agg\n",
    "\n",
    "sns.set(color_codes=True)\n",
    "sns.set_style(\"darkgrid\")\n",
    "\n",
    "print \"The dataset contains %s unique subreddits.\" % len(sf['subreddit'].unique())\n",
    "g = sf.groupby('subreddit', {'posts_num': agg.COUNT()})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5af854fd90>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5af84bc110>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(g['posts_num'],bins=20, axlabel=\"posts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 371,833 subreddits in the dataset. From the above histogram, we can see that the overwhelming majority of subreddits have very few posts. Let's look at the histogram of subreddits with at least a million posts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "357 subreddits with at least a million posts\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f5a84108ed0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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EMwC4TBDWUaTlhCiSmo9ZMwwOADGNsI4iLSdEkaR4N8PgAHA5IKyjSJ0/KEmKj2sIaYfD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\nCGsAAAz3/wHrK+kYL4ZYRwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5a64301190>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g_mil = g[g['posts_num'] >= 1000000]\n",
    "print \"%s subreddits with at least a million posts\" % len(g_mil)\n",
    "sns.distplot(g_mil['posts_num'], axlabel=\"posts\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We discover that only 357 subreddits, less 0.1% of all the subreddits, contain more than a million posts. Let's calculate how many posts these subreddits contain in total."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The most popular subreddits contain 1629867408 posts\n"
     ]
    }
   ],
   "source": [
    "print \"The most popular subreddits contain %s posts\" % g_mil['posts_num'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most popular subreddits contain over 1.62 billion posts. In other words, less than 0.1% of the subreddits contain 68.2% of the posts. This result reminds me of the fact that over 57% of the world's population lives in the ten most populous [countries](https://en.wikipedia.org/wiki/World_population).\n",
    "Let's map the users' activity in each subbreddit. Namely, we will find how many distinct user names there are in each subreddit, and what subreddits have the most unique users."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+----------------------+-------------------------+\n",
      "|      subreddit       | distinct_authors_number |\n",
      "+----------------------+-------------------------+\n",
      "|      AskReddit       |         5465755         |\n",
      "|        funny         |         3204002         |\n",
      "|         pics         |         3076198         |\n",
      "|         IAmA         |         2155718         |\n",
      "|        gaming        |         2059042         |\n",
      "|        videos        |         2021998         |\n",
      "|         WTF          |         1962940         |\n",
      "|    todayilearned     |         1902033         |\n",
      "|    AdviceAnimals     |         1679658         |\n",
      "|         aww          |         1525875         |\n",
      "|      worldnews       |         1503139         |\n",
      "|        movies        |         1341623         |\n",
      "|         gifs         |         1327207         |\n",
      "|        Music         |         1265940         |\n",
      "|         news         |         1120131         |\n",
      "|       politics       |         1078397         |\n",
      "|   leagueoflegends    |          909849         |\n",
      "|    Showerthoughts    |          903086         |\n",
      "|       atheism        |          900926         |\n",
      "|  mildlyinteresting   |          897297         |\n",
      "|      technology      |          874948         |\n",
      "|  explainlikeimfive   |          872558         |\n",
      "|      reddit.com      |          836257         |\n",
      "|        trees         |          791134         |\n",
      "|       science        |          699283         |\n",
      "|         tifu         |          627500         |\n",
      "|     pcmasterrace     |          601513         |\n",
      "|     LifeProTips      |          591906         |\n",
      "|        books         |          566367         |\n",
      "|       gonewild       |          552611         |\n",
      "|       Fitness        |          551939         |\n",
      "|         food         |          513428         |\n",
      "|    relationships     |          506711         |\n",
      "|      television      |          492369         |\n",
      "| fffffffuuuuuuuuuuuu  |          475221         |\n",
      "|        Jokes         |          458080         |\n",
      "|         sex          |          452290         |\n",
      "|   TwoXChromosomes    |          451801         |\n",
      "|     nottheonion      |          447415         |\n",
      "|   personalfinance    |          435008         |\n",
      "|        creepy        |          433207         |\n",
      "|       buildapc       |          423400         |\n",
      "|       pokemon        |          417395         |\n",
      "|      cringepics      |          379199         |\n",
      "|    OldSchoolCool     |          378328         |\n",
      "|        sports        |          375538         |\n",
      "|         DIY          |          369555         |\n",
      "|   GlobalOffensive    |          356078         |\n",
      "|      Overwatch       |          353248         |\n",
      "|      pokemongo       |          348015         |\n",
      "|      Minecraft       |          346610         |\n",
      "|    gameofthrones     |          342183         |\n",
      "|       woahdude       |          342034         |\n",
      "|      EarthPorn       |          331829         |\n",
      "|        Games         |          327470         |\n",
      "|         nfl          |          323519         |\n",
      "|     hearthstone      |          318704         |\n",
      "|       Android        |          314916         |\n",
      "|      askscience      |          313791         |\n",
      "|        DotA2         |          309898         |\n",
      "|        bestof        |          309743         |\n",
      "|        soccer        |          309067         |\n",
      "|         wow          |          305485         |\n",
      "|     friendsafari     |          298996         |\n",
      "|      Futurology      |          294915         |\n",
      "|   dataisbeautiful    |          289916         |\n",
      "|     GetMotivated     |          288994         |\n",
      "|         nba          |          285947         |\n",
      "|     reactiongifs     |          282759         |\n",
      "|  malefashionadvice   |          279534         |\n",
      "|        4chan         |          274217         |\n",
      "|        space         |          272824         |\n",
      "|    DestinyTheGame    |          265169         |\n",
      "|  millionairemakers   |          263846         |\n",
      "|       nosleep        |          259567         |\n",
      "|  interestingasfuck   |          259040         |\n",
      "| ImGoingToHellForThis |          258763         |\n",
      "|         Art          |          251100         |\n",
      "|    tipofmytongue     |          250919         |\n",
      "|        cringe        |          248369         |\n",
      "|        skyrim        |          247361         |\n",
      "|      circlejerk      |          246957         |\n",
      "|     techsupport      |          242859         |\n",
      "|  BlackPeopleTwitter  |          241724         |\n",
      "|   photoshopbattles   |          235111         |\n",
      "|        anime         |          233713         |\n",
      "|       StarWars       |          233363         |\n",
      "|      The_Donald      |          232584         |\n",
      "|        AskMen        |          231575         |\n",
      "|        promos        |          227740         |\n",
      "|       gadgets        |          227630         |\n",
      "|    Documentaries     |          227155         |\n",
      "|     hiphopheads      |          224751         |\n",
      "|        Frugal        |          223954         |\n",
      "|         nsfw         |          218661         |\n",
      "|    TumblrInAction    |          217394         |\n",
      "|       Fallout        |          216836         |\n",
      "|     programming      |          215156         |\n",
      "|        Steam         |          214232         |\n",
      "|         PS4          |          214131         |\n",
      "+----------------------+-------------------------+\n",
      "[371833 rows x 2 columns]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "g = sf.groupby('subreddit', {'distinct_authors_number':agg.COUNT_DISTINCT('author')})\n",
    "g = g.sort('distinct_authors_number', ascending=False)\n",
    "g.print_rows(100)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By calculating the elapsed time between users' first post and last post, we can also estimate how much time users have been active in each subreddit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\"><table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">author</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">subreddit</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">start_date</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">end_date</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">posts_num</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">activity_time</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">d4mini0n</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">ainbow</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1334038071</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1427931191</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">9</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">93893120</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">polinreddit</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">news</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1325830586</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1325830586</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">goliveyourdreams</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">relationships</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1337470570</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1451506045</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">27</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">114035475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">ssa111</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">spreading</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1448388980</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1451500948</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3111968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">SugarBeets</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">malelivingspace</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1356540644</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1474085882</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">20</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">117545238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Wejurt</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">canucks</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1429683528</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1430083478</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">8</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">399950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">themonthofmae</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">relationships</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1468165432</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1468165480</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Puckhead7</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">ColoradoAvalanche</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1419580278</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1476590616</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">43</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">57010338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">throwitawaytrustme</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">relationships</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1448225775</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1448225775</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">spinstartshere</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Lenovo</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1455307194</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1456503969</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1196775</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[170259623 rows x 6 columns]<br/>Note: Only the head of the SFrame is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tauthor\tstr\n",
       "\tsubreddit\tstr\n",
       "\tstart_date\tint\n",
       "\tend_date\tint\n",
       "\tposts_num\tint\n",
       "\tactivity_time\tint\n",
       "\n",
       "Rows: 170259623\n",
       "\n",
       "Data:\n",
       "+--------------------+-------------------+------------+------------+-----------+\n",
       "|       author       |     subreddit     | start_date |  end_date  | posts_num |\n",
       "+--------------------+-------------------+------------+------------+-----------+\n",
       "|      d4mini0n      |       ainbow      | 1334038071 | 1427931191 |     9     |\n",
       "|    polinreddit     |        news       | 1325830586 | 1325830586 |     1     |\n",
       "|  goliveyourdreams  |   relationships   | 1337470570 | 1451506045 |     27    |\n",
       "|       ssa111       |     spreading     | 1448388980 | 1451500948 |     2     |\n",
       "|     SugarBeets     |  malelivingspace  | 1356540644 | 1474085882 |     20    |\n",
       "|       Wejurt       |      canucks      | 1429683528 | 1430083478 |     8     |\n",
       "|   themonthofmae    |   relationships   | 1468165432 | 1468165480 |     2     |\n",
       "|     Puckhead7      | ColoradoAvalanche | 1419580278 | 1476590616 |     43    |\n",
       "| throwitawaytrustme |   relationships   | 1448225775 | 1448225775 |     1     |\n",
       "|   spinstartshere   |       Lenovo      | 1455307194 | 1456503969 |     3     |\n",
       "+--------------------+-------------------+------------+------------+-----------+\n",
       "+---------------+\n",
       "| activity_time |\n",
       "+---------------+\n",
       "|    93893120   |\n",
       "|       0       |\n",
       "|   114035475   |\n",
       "|    3111968    |\n",
       "|   117545238   |\n",
       "|     399950    |\n",
       "|       48      |\n",
       "|    57010338   |\n",
       "|       0       |\n",
       "|    1196775    |\n",
       "+---------------+\n",
       "[170259623 rows x 6 columns]\n",
       "Note: Only the head of the SFrame is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Important: running the following code block may take considerable time\n",
    "sf['created_utc'] = sf['created_utc'].astype(int)\n",
    "subreddit_users = sf.groupby(['subreddit', 'author'], {'start_date':agg.MIN('created_utc'), 'end_date': agg.MAX('created_utc'), 'posts_num':agg.COUNT()} )\n",
    "subreddit_users['activity_time'] = subreddit_users.apply(lambda d: d['end_date'] - d['start_date'])\n",
    "subreddit_users"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's calculate the average time users have been active in each subreddit. To understand the activity time distribution across the subreddits, let's plot a histogram of average activity time."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f93f80df8d0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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zdCT0ez6IzvCoAABzwbI/YgfgeWeY3Bv73tWxgTRJ0g+f+52WLklT+eX5Sfv1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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9574540890>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = subreddit_users.groupby('subreddit', {'avg_active_time_in_seconds': agg.AVG('activity_time')})\n",
    "g['avg_active_time_in_days'] = g['avg_active_time_in_seconds'].apply(lambda sec: sec/(60.0*60.0*24))\n",
    "sns.distplot(g['avg_active_time_in_days'], axlabel=\"days\", bins=20 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\n",
       "+--------------------+---------------+----------+\n",
       "|        item        |     value     | is exact |\n",
       "+--------------------+---------------+----------+\n",
       "|       Length       |     371833    |   Yes    |\n",
       "|        Min         |      0.0      |   Yes    |\n",
       "|        Max         | 2208.85173611 |   Yes    |\n",
       "|        Mean        | 24.0121476349 |   Yes    |\n",
       "|        Sum         | 8928508.89152 |   Yes    |\n",
       "|      Variance      | 3906.78028205 |   Yes    |\n",
       "| Standard Deviation | 62.5042421124 |   Yes    |\n",
       "|  # Missing Values  |       0       |   Yes    |\n",
       "|  # unique values   |     201266    |    No    |\n",
       "+--------------------+---------------+----------+\n",
       "\n",
       "Most frequent items:\n",
       "+-------+--------+-------------------+-------------------+-------------------+\n",
       "| value |  0.0   | 2.31481481481e-05 | 6.94444444444e-05 | 1.15740740741e-05 |\n",
       "+-------+--------+-------------------+-------------------+-------------------+\n",
       "| count | 154663 |        383        |        381        |        372        |\n",
       "+-------+--------+-------------------+-------------------+-------------------+\n",
       "+-------------------+-------------------+-------------------+-------------------+\n",
       "| 3.47222222222e-05 | 4.62962962963e-05 | 5.78703703704e-05 | 8.10185185185e-05 |\n",
       "+-------------------+-------------------+-------------------+-------------------+\n",
       "|        350        |        250        |        235        |        182        |\n",
       "+-------------------+-------------------+-------------------+-------------------+\n",
       "+-------------------+-------------------+\n",
       "| 1.73611111111e-05 | 9.25925925926e-05 |\n",
       "+-------------------+-------------------+\n",
       "|        155        |        148        |\n",
       "+-------------------+-------------------+\n",
       "\n",
       "Quantiles: \n",
       "+-----+-----+-----+-----+-----------------+---------------+---------------+\n",
       "|  0% |  1% |  5% | 25% |       50%       |      75%      |      95%      |\n",
       "+-----+-----+-----+-----+-----------------+---------------+---------------+\n",
       "| 0.0 | 0.0 | 0.0 | 0.0 | 0.0447029320988 | 18.2136749847 | 130.748425926 |\n",
       "+-----+-----+-----+-----+-----------------+---------------+---------------+\n",
       "+---------------+---------------+\n",
       "|      99%      |      100%     |\n",
       "+---------------+---------------+\n",
       "| 277.742471065 | 2208.85173611 |\n",
       "+---------------+---------------+"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g['avg_active_time_in_days'].sketch_summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see from the above results that most of the subreddits' users are active for a very limited time, with an average of less than a month and a median of less than a day."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3. Join-Rate Curves"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our [study](http://dynamics.cs.washington.edu/publications.html), we focused on analyzing the various patterns in which users join each subreddit (also referred to as the Join-Rate-Curve). In this section, we present the code that was used to create these curves. To create the join-rate-curve of each subreddit, we first created a TimeSeries object with the subreddit information. Throughout this section, we will use the [_Science_ subreddit](https://www.reddit.com/r/science/)  as an example.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">It sort of sounds like<br>the caffeinated-baby  ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">The 10 year old inside me<br>chuckled at \"pinches off ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">One would think a<br>journalist (or even a ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">almost useful!\\r\\n\\r\\nFor<br>me, in computer science, ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">An entertaining rant.<br>Definitely worth a ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">:)</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">No, but you just gave me<br>the idea to do so. ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">that is fascinating. i<br>wonder how long before ...</td>\n",
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       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">Or, at least, bolder,<br>which is a trait that ...</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1161204394</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">null</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">cmrsx</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t3_mpuf</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t1_cmqc1</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1473802603</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1161205779</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">null</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">cmrxx</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t3_mqcp</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t3_mqcp</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1473802605</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">stickied</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">subreddit</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">subreddit_id</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">ups</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">month</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">year</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">banned_by</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">replies</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">removal_reason</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">likes</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">user_reports</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">7</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">3</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">4</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">1</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">false</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">science</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">t5_mouw</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">0</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">10</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">2006</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">saved</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">archived</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">report_reasons</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">approved_by</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">downs</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">body_html</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">score_hidden</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">name</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">created</th>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">mod_reports</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "</table>\n",
       "<table frame=\"box\" rules=\"cols\">\n",
       "    <tr>\n",
       "        <th style=\"padding-left: 1em; padding-right: 1em; text-align: center\">num_reports</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "        <td style=\"padding-left: 1em; padding-right: 1em; text-align: center; vertical-align: top\">None</td>\n",
       "    </tr>\n",
       "</table>\n",
       "[4975855 rows x 37 columns]<br/>Note: Only the head of the TimeSeries is printed.<br/>You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns.\n",
       "</div>"
      ],
      "text/plain": [
       "Columns:\n",
       "\tdatetime\tdatetime (index column)\n",
       "\tauthor\tstr\n",
       "\tauthor_flair_css_class\tstr\n",
       "\tauthor_flair_text\tstr\n",
       "\tbody\tstr\n",
       "\tcontroversiality\tstr\n",
       "\tcreated_utc\tstr\n",
       "\tdistinguished\tstr\n",
       "\tedited\tstr\n",
       "\tgilded\tstr\n",
       "\tid\tstr\n",
       "\tlink_id\tstr\n",
       "\tparent_id\tstr\n",
       "\tretrieved_on\tstr\n",
       "\tscore\tstr\n",
       "\tstickied\tstr\n",
       "\tsubreddit\tstr\n",
       "\tsubreddit_id\tstr\n",
       "\tups\tstr\n",
       "\tmonth\tstr\n",
       "\tyear\tstr\n",
       "\tbanned_by\tstr\n",
       "\treplies\tstr\n",
       "\tremoval_reason\tstr\n",
       "\tlikes\tstr\n",
       "\tuser_reports\tstr\n",
       "\tsaved\tstr\n",
       "\tarchived\tstr\n",
       "\treport_reasons\tstr\n",
       "\tapproved_by\tstr\n",
       "\tdowns\tstr\n",
       "\tbody_html\tstr\n",
       "\tscore_hidden\tstr\n",
       "\tname\tstr\n",
       "\tcreated\tstr\n",
       "\tmod_reports\tstr\n",
       "\tnum_reports\tstr\n",
       "\n",
       "Rows: 4975855\n",
       "\n",
       "Data:\n",
       "+---------------------+----------------+------------------------+\n",
       "|       datetime      |     author     | author_flair_css_class |\n",
       "+---------------------+----------------+------------------------+\n",
       "| 2006-10-18 16:36:27 |   conrad_hex   |          null          |\n",
       "| 2006-10-18 16:56:54 |  the_seanald   |          null          |\n",
       "| 2006-10-18 17:07:48 | Mr_Smartypants |          null          |\n",
       "| 2006-10-18 17:10:15 |     tcervl     |          null          |\n",
       "| 2006-10-18 17:18:07 |  Lagged2Death  |          null          |\n",
       "| 2006-10-18 18:37:48 |   anonymgrl    |          null          |\n",
       "| 2006-10-18 19:13:51 |   Saintstace   |          null          |\n",
       "| 2006-10-18 19:30:02 |    _jjsonp     |          null          |\n",
       "| 2006-10-18 20:46:34 |    dsandler    |          null          |\n",
       "| 2006-10-18 21:09:39 |   NitsujTPU    |        compsci         |\n",
       "+---------------------+----------------+------------------------+\n",
       "+------------------------+-------------------------------+------------------+\n",
       "|   author_flair_text    |              body             | controversiality |\n",
       "+------------------------+-------------------------------+------------------+\n",
       "|          null          | It sort of sounds like the... |        0         |\n",
       "|          null          | The 10 year old inside me ... |        0         |\n",
       "|          null          | One would think a journali... |        0         |\n",
       "|          null          | almost useful!\\r\\n\\r\\nFor ... |        0         |\n",
       "|          null          | An entertaining rant. Defi... |        0         |\n",
       "|          null          |               :)              |        1         |\n",
       "|          null          | No, but you just gave me t... |        0         |\n",
       "|          null          | that is fascinating. i won... |        0         |\n",
       "|          null          | Or, at least, bolder, whic... |        0         |\n",
       "| PhD | Computer Science | Mind Hacks is awesome.  Th... |        0         |\n",
       "+------------------------+-------------------------------+------------------+\n",
       "+-------------+---------------+--------+--------+-------+---------+-----------+\n",
       "| created_utc | distinguished | edited | gilded |   id  | link_id | parent_id |\n",
       "+-------------+---------------+--------+--------+-------+---------+-----------+\n",
       "|  1161189387 |      null     | false  |   0    | cmqc1 | t3_mpuf |  t3_mpuf  |\n",
       "|  1161190614 |      null     | false  |   0    | cmqf7 | t3_mp5w |  t3_mp5w  |\n",
       "|  1161191268 |      null     | false  |   0    | cmqha | t3_mpuf |  t3_mpuf  |\n",
       "|  1161191415 |      null     | false  |   0    | cmqhk | t3_mppf |  t3_mppf  |\n",
       "|  1161191887 |      null     | false  |   0    | cmqiv | t3_mpjm |  t3_mpjm  |\n",
       "|  1161196668 |      null     | false  |   0    | cmqyw | t3_mp5w |  t1_cmqf7 |\n",
       "|  1161198831 |      null     | false  |   0    | cmr6f | t3_mr3t |  t3_mr3t  |\n",
       "|  1161199802 |      null     | false  |   0    | cmrbo | t3_mp5w |  t3_mp5w  |\n",
       "|  1161204394 |      null     | false  |   0    | cmrsx | t3_mpuf |  t1_cmqc1 |\n",
       "|  1161205779 |      null     | false  |   0    | cmrxx | t3_mqcp |  t3_mqcp  |\n",
       "+-------------+---------------+--------+--------+-------+---------+-----------+\n",
       "+--------------+-------+----------+-----------+--------------+-----+-------+-----+\n",
       "| retrieved_on | score | stickied | subreddit | subreddit_id | ups | month | ... |\n",
       "+--------------+-------+----------+-----------+--------------+-----+-------+-----+\n",
       "|  1473802574  |   2   |  false   |  science  |   t5_mouw    |  2  |   10  | ... |\n",
       "|  1473802577  |   7   |  false   |  science  |   t5_mouw    |  7  |   10  | ... |\n",
       "|  1473802577  |   2   |  false   |  science  |   t5_mouw    |  2  |   10  | ... |\n",
       "|  1473802577  |   3   |  false   |  science  |   t5_mouw    |  3  |   10  | ... |\n",
       "|  1473802578  |   4   |  false   |  science  |   t5_mouw    |  4  |   10  | ... |\n",
       "|  1473802587  |   2   |  false   |  science  |   t5_mouw    |  2  |   10  | ... |\n",
       "|  1473802591  |   3   |  false   |  science  |   t5_mouw    |  3  |   10  | ... |\n",
       "|  1473802593  |   4   |  false   |  science  |   t5_mouw    |  4  |   10  | ... |\n",
       "|  1473802603  |   1   |  false   |  science  |   t5_mouw    |  1  |   10  | ... |\n",
       "|  1473802605  |   0   |  false   |  science  |   t5_mouw    |  0  |   10  | ... |\n",
       "+--------------+-------+----------+-----------+--------------+-----+-------+-----+\n",
       "[4975855 rows x 37 columns]\n",
       "Note: Only the head of the TimeSeries is printed.\n",
       "You can use print_rows(num_rows=m, num_columns=n) to print more rows and columns."
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from datetime import datetime, timedelta\n",
    "\n",
    "science_sf = sf[sf['subreddit'] =='science']\n",
    "science_sf['datetime'] = science_sf['created_utc'].apply(lambda utc:datetime.utcfromtimestamp(int(utc)))\n",
    "subreddit_ts = gl.TimeSeries(science_sf, index='datetime')\n",
    "subreddit_ts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use the following function to create the subreddit user arrival curve from the TimeSeries object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Calculating the user arrival curve between 2006-10-18 16:36:27 and 2006-11-15 16:36:27\n",
      "Calculating the user arrival curve between 2006-11-15 16:36:27 and 2006-12-13 16:36:27\n",
      "Calculating the user arrival curve between 2006-12-13 16:36:27 and 2007-01-10 16:36:27\n",
      "Calculating the user arrival curve between 2007-01-10 16:36:27 and 2007-02-07 16:36:27\n",
      "Calculating the user arrival curve between 2007-02-07 16:36:27 and 2007-03-07 16:36:27\n",
      "Calculating the user arrival curve between 2007-03-07 16:36:27 and 2007-04-04 16:36:27\n",
      "Calculating the user arrival curve between 2007-04-04 16:36:27 and 2007-05-02 16:36:27\n",
      "Calculating the user arrival curve between 2007-05-02 16:36:27 and 2007-05-30 16:36:27\n",
      "Calculating the user arrival curve between 2007-05-30 16:36:27 and 2007-06-27 16:36:27\n",
      "Calculating the user arrival curve between 2007-06-27 16:36:27 and 2007-07-25 16:36:27\n",
      "Calculating the user arrival curve between 2007-07-25 16:36:27 and 2007-08-22 16:36:27\n",
      "Calculating the user arrival curve between 2007-08-22 16:36:27 and 2007-09-19 16:36:27\n",
      "Calculating the user arrival curve between 2007-09-19 16:36:27 and 2007-10-17 16:36:27\n",
      "Calculating the user arrival curve between 2007-10-17 16:36:27 and 2007-11-14 16:36:27\n",
      "Calculating the user arrival curve between 2007-11-14 16:36:27 and 2007-12-12 16:36:27\n",
      "Calculating the user arrival curve between 2007-12-12 16:36:27 and 2008-01-09 16:36:27\n",
      "Calculating the user arrival curve between 2008-01-09 16:36:27 and 2008-02-06 16:36:27\n",
      "Calculating the user arrival curve between 2008-02-06 16:36:27 and 2008-03-05 16:36:27\n",
      "Calculating the user arrival curve between 2008-03-05 16:36:27 and 2008-04-02 16:36:27\n",
      "Calculating the user arrival curve between 2008-04-02 16:36:27 and 2008-04-30 16:36:27\n",
      "Calculating the user arrival curve between 2008-04-30 16:36:27 and 2008-05-28 16:36:27\n",
      "Calculating the user arrival curve between 2008-05-28 16:36:27 and 2008-06-25 16:36:27\n",
      "Calculating the user arrival curve between 2008-06-25 16:36:27 and 2008-07-23 16:36:27\n",
      "Calculating the user arrival curve between 2008-07-23 16:36:27 and 2008-08-20 16:36:27\n",
      "Calculating the user arrival curve between 2008-08-20 16:36:27 and 2008-09-17 16:36:27\n",
      "Calculating the user arrival curve between 2008-09-17 16:36:27 and 2008-10-15 16:36:27\n",
      "Calculating the user arrival curve between 2008-10-15 16:36:27 and 2008-11-12 16:36:27\n",
      "Calculating the user arrival curve between 2008-11-12 16:36:27 and 2008-12-10 16:36:27\n",
      "Calculating the user arrival curve between 2008-12-10 16:36:27 and 2009-01-07 16:36:27\n",
      "Calculating the user arrival curve between 2009-01-07 16:36:27 and 2009-02-04 16:36:27\n",
      "Calculating the user arrival curve between 2009-02-04 16:36:27 and 2009-03-04 16:36:27\n",
      "Calculating the user arrival curve between 2009-03-04 16:36:27 and 2009-04-01 16:36:27\n",
      "Calculating the user arrival curve between 2009-04-01 16:36:27 and 2009-04-29 16:36:27\n",
      "Calculating the user arrival curve between 2009-04-29 16:36:27 and 2009-05-27 16:36:27\n",
      "Calculating the user arrival curve between 2009-05-27 16:36:27 and 2009-06-24 16:36:27\n",
      "Calculating the user arrival curve between 2009-06-24 16:36:27 and 2009-07-22 16:36:27\n",
      "Calculating the user arrival curve between 2009-07-22 16:36:27 and 2009-08-19 16:36:27\n",
      "Calculating the user arrival curve between 2009-08-19 16:36:27 and 2009-09-16 16:36:27\n",
      "Calculating the user arrival curve between 2009-09-16 16:36:27 and 2009-10-14 16:36:27\n",
      "Calculating the user arrival curve between 2009-10-14 16:36:27 and 2009-11-11 16:36:27\n",
      "Calculating the user arrival curve between 2009-11-11 16:36:27 and 2009-12-09 16:36:27\n",
      "Calculating the user arrival curve between 2009-12-09 16:36:27 and 2010-01-06 16:36:27\n",
      "Calculating the user arrival curve between 2010-01-06 16:36:27 and 2010-02-03 16:36:27\n",
      "Calculating the user arrival curve between 2010-02-03 16:36:27 and 2010-03-03 16:36:27\n",
      "Calculating the user arrival curve between 2010-03-03 16:36:27 and 2010-03-31 16:36:27\n",
      "Calculating the user arrival curve between 2010-03-31 16:36:27 and 2010-04-28 16:36:27\n",
      "Calculating the user arrival curve between 2010-04-28 16:36:27 and 2010-05-26 16:36:27\n",
      "Calculating the user arrival curve between 2010-05-26 16:36:27 and 2010-06-23 16:36:27\n",
      "Calculating the user arrival curve between 2010-06-23 16:36:27 and 2010-07-21 16:36:27\n",
      "Calculating the user arrival curve between 2010-07-21 16:36:27 and 2010-08-18 16:36:27\n",
      "Calculating the user arrival curve between 2010-08-18 16:36:27 and 2010-09-15 16:36:27\n",
      "Calculating the user arrival curve between 2010-09-15 16:36:27 and 2010-10-13 16:36:27\n",
      "Calculating the user arrival curve between 2010-10-13 16:36:27 and 2010-11-10 16:36:27\n",
      "Calculating the user arrival curve between 2010-11-10 16:36:27 and 2010-12-08 16:36:27\n",
      "Calculating the user arrival curve between 2010-12-08 16:36:27 and 2011-01-05 16:36:27\n",
      "Calculating the user arrival curve between 2011-01-05 16:36:27 and 2011-02-02 16:36:27\n",
      "Calculating the user arrival curve between 2011-02-02 16:36:27 and 2011-03-02 16:36:27\n",
      "Calculating the user arrival curve between 2011-03-02 16:36:27 and 2011-03-30 16:36:27\n",
      "Calculating the user arrival curve between 2011-03-30 16:36:27 and 2011-04-27 16:36:27\n",
      "Calculating the user arrival curve between 2011-04-27 16:36:27 and 2011-05-25 16:36:27\n",
      "Calculating the user arrival curve between 2011-05-25 16:36:27 and 2011-06-22 16:36:27\n",
      "Calculating the user arrival curve between 2011-06-22 16:36:27 and 2011-07-20 16:36:27\n",
      "Calculating the user arrival curve between 2011-07-20 16:36:27 and 2011-08-17 16:36:27\n",
      "Calculating the user arrival curve between 2011-08-17 16:36:27 and 2011-09-14 16:36:27\n",
      "Calculating the user arrival curve between 2011-09-14 16:36:27 and 2011-10-12 16:36:27\n",
      "Calculating the user arrival curve between 2011-10-12 16:36:27 and 2011-11-09 16:36:27\n",
      "Calculating the user arrival curve between 2011-11-09 16:36:27 and 2011-12-07 16:36:27\n",
      "Calculating the user arrival curve between 2011-12-07 16:36:27 and 2012-01-04 16:36:27\n",
      "Calculating the user arrival curve between 2012-01-04 16:36:27 and 2012-02-01 16:36:27\n",
      "Calculating the user arrival curve between 2012-02-01 16:36:27 and 2012-02-29 16:36:27\n",
      "Calculating the user arrival curve between 2012-02-29 16:36:27 and 2012-03-28 16:36:27\n",
      "Calculating the user arrival curve between 2012-03-28 16:36:27 and 2012-04-25 16:36:27\n",
      "Calculating the user arrival curve between 2012-04-25 16:36:27 and 2012-05-23 16:36:27\n",
      "Calculating the user arrival curve between 2012-05-23 16:36:27 and 2012-06-20 16:36:27\n",
      "Calculating the user arrival curve between 2012-06-20 16:36:27 and 2012-07-18 16:36:27\n",
      "Calculating the user arrival curve between 2012-07-18 16:36:27 and 2012-08-15 16:36:27\n",
      "Calculating the user arrival curve between 2012-08-15 16:36:27 and 2012-09-12 16:36:27\n",
      "Calculating the user arrival curve between 2012-09-12 16:36:27 and 2012-10-10 16:36:27\n",
      "Calculating the user arrival curve between 2012-10-10 16:36:27 and 2012-11-07 16:36:27\n",
      "Calculating the user arrival curve between 2012-11-07 16:36:27 and 2012-12-05 16:36:27\n",
      "Calculating the user arrival curve between 2012-12-05 16:36:27 and 2013-01-02 16:36:27\n",
      "Calculating the user arrival curve between 2013-01-02 16:36:27 and 2013-01-30 16:36:27\n",
      "Calculating the user arrival curve between 2013-01-30 16:36:27 and 2013-02-27 16:36:27\n",
      "Calculating the user arrival curve between 2013-02-27 16:36:27 and 2013-03-27 16:36:27\n",
      "Calculating the user arrival curve between 2013-03-27 16:36:27 and 2013-04-24 16:36:27\n",
      "Calculating the user arrival curve between 2013-04-24 16:36:27 and 2013-05-22 16:36:27\n",
      "Calculating the user arrival curve between 2013-05-22 16:36:27 and 2013-06-19 16:36:27\n",
      "Calculating the user arrival curve between 2013-06-19 16:36:27 and 2013-07-17 16:36:27\n",
      "Calculating the user arrival curve between 2013-07-17 16:36:27 and 2013-08-14 16:36:27\n",
      "Calculating the user arrival curve between 2013-08-14 16:36:27 and 2013-09-11 16:36:27\n",
      "Calculating the user arrival curve between 2013-09-11 16:36:27 and 2013-10-09 16:36:27\n",
      "Calculating the user arrival curve between 2013-10-09 16:36:27 and 2013-11-06 16:36:27\n",
      "Calculating the user arrival curve between 2013-11-06 16:36:27 and 2013-12-04 16:36:27\n",
      "Calculating the user arrival curve between 2013-12-04 16:36:27 and 2014-01-01 16:36:27\n",
      "Calculating the user arrival curve between 2014-01-01 16:36:27 and 2014-01-29 16:36:27\n",
      "Calculating the user arrival curve between 2014-01-29 16:36:27 and 2014-02-26 16:36:27\n",
      "Calculating the user arrival curve between 2014-02-26 16:36:27 and 2014-03-26 16:36:27\n",
      "Calculating the user arrival curve between 2014-03-26 16:36:27 and 2014-04-23 16:36:27\n",
      "Calculating the user arrival curve between 2014-04-23 16:36:27 and 2014-05-21 16:36:27\n",
      "Calculating the user arrival curve between 2014-05-21 16:36:27 and 2014-06-18 16:36:27\n",
      "Calculating the user arrival curve between 2014-06-18 16:36:27 and 2014-07-16 16:36:27\n",
      "Calculating the user arrival curve between 2014-07-16 16:36:27 and 2014-08-13 16:36:27\n",
      "Calculating the user arrival curve between 2014-08-13 16:36:27 and 2014-09-10 16:36:27\n",
      "Calculating the user arrival curve between 2014-09-10 16:36:27 and 2014-10-08 16:36:27\n",
      "Calculating the user arrival curve between 2014-10-08 16:36:27 and 2014-11-05 16:36:27\n",
      "Calculating the user arrival curve between 2014-11-05 16:36:27 and 2014-12-03 16:36:27\n",
      "Calculating the user arrival curve between 2014-12-03 16:36:27 and 2014-12-31 16:36:27\n",
      "Calculating the user arrival curve between 2014-12-31 16:36:27 and 2015-01-28 16:36:27\n",
      "Calculating the user arrival curve between 2015-01-28 16:36:27 and 2015-02-25 16:36:27\n",
      "Calculating the user arrival curve between 2015-02-25 16:36:27 and 2015-03-25 16:36:27\n",
      "Calculating the user arrival curve between 2015-03-25 16:36:27 and 2015-04-22 16:36:27\n",
      "Calculating the user arrival curve between 2015-04-22 16:36:27 and 2015-05-20 16:36:27\n",
      "Calculating the user arrival curve between 2015-05-20 16:36:27 and 2015-06-17 16:36:27\n",
      "Calculating the user arrival curve between 2015-06-17 16:36:27 and 2015-07-15 16:36:27\n",
      "Calculating the user arrival curve between 2015-07-15 16:36:27 and 2015-08-12 16:36:27\n",
      "Calculating the user arrival curve between 2015-08-12 16:36:27 and 2015-09-09 16:36:27\n",
      "Calculating the user arrival curve between 2015-09-09 16:36:27 and 2015-10-07 16:36:27\n",
      "Calculating the user arrival curve between 2015-10-07 16:36:27 and 2015-11-04 16:36:27\n",
      "Calculating the user arrival curve between 2015-11-04 16:36:27 and 2015-12-02 16:36:27\n",
      "Calculating the user arrival curve between 2015-12-02 16:36:27 and 2015-12-30 16:36:27\n",
      "Calculating the user arrival curve between 2015-12-30 16:36:27 and 2016-01-27 16:36:27\n",
      "Calculating the user arrival curve between 2016-01-27 16:36:27 and 2016-02-24 16:36:27\n",
      "Calculating the user arrival curve between 2016-02-24 16:36:27 and 2016-03-23 16:36:27\n",
      "Calculating the user arrival curve between 2016-03-23 16:36:27 and 2016-04-20 16:36:27\n",
      "Calculating the user arrival curve between 2016-04-20 16:36:27 and 2016-05-18 16:36:27\n",
      "Calculating the user arrival curve between 2016-05-18 16:36:27 and 2016-06-15 16:36:27\n",
      "Calculating the user arrival curve between 2016-06-15 16:36:27 and 2016-07-13 16:36:27\n",
      "Calculating the user arrival curve between 2016-07-13 16:36:27 and 2016-08-10 16:36:27\n",
      "Calculating the user arrival curve between 2016-08-10 16:36:27 and 2016-09-07 16:36:27\n",
      "Calculating the user arrival curve between 2016-09-07 16:36:27 and 2016-10-05 16:36:27\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "def get_subreddit_users_arrival_curve(subreddit_ts, weeks_number=4):\n",
    "    \"\"\"\n",
    "    Calculates the percent of authors that joined after X weeks from all authors that joined the subreddit\n",
    "    between the date of the first comment and the date of the last comment\n",
    "    :param subreddit_ts: TimeSeries with the subreddit posts information\n",
    "    :param weeks_number: the number of weeks to set the time-interval between each two calculations\n",
    "    :return: dict in which all the keys are the number of weeks since the first comment was posted and the\n",
    "        corresponding percentage of authors that joined the subreddit up until this week\n",
    "    :rtype: dict\n",
    "    \"\"\"\n",
    "    dt = subreddit_ts.min_time\n",
    "    end_dt = subreddit_ts.max_time\n",
    "    authors = set()\n",
    "    d = {0: 0}\n",
    "    td = timedelta(days=7 * weeks_number)\n",
    "    count = 1\n",
    "    total_authors_num = float(len(subreddit_ts['author'].unique()))    \n",
    "    while dt + td <= end_dt:\n",
    "        ts = subreddit_ts.slice(dt, dt + td)\n",
    "        authors |= set(ts['author'])\n",
    "        print \"Calculating the user arrival curve between %s and %s\" % (dt, dt + td) \n",
    "        dt += td\n",
    "        d[count * weeks_number] = len(authors) / total_authors_num\n",
    "        count += 1\n",
    "    ts = subreddit_ts.slice(dt, subreddit_ts.max_time)\n",
    "    authors |= set(ts['author'])\n",
    "    subreddit_age = subreddit_ts.max_time - subreddit_ts.min_time\n",
    "    d[math.ceil(     subreddit_age.days/ 7.0)] = len(\n",
    "        authors) / total_authors_num  # round the number of weeks up mainly for drawing the graph\n",
    "    return d\n",
    "d = get_subreddit_users_arrival_curve(subreddit_ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x7f93d8055290>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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W1mDZxnPQ6014blo0YiP8pY5Eds5R6gBERLamsLwe760/i+YWA+Yk9MOQviqpIxGx8ImI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\nC5+IiMgO/D+Qsjyel9nO5wAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f951c72a450>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "keys = d.keys()\n",
    "keys.sort()\n",
    "values = [d[k] for k in keys]\n",
    "plt.plot(keys, values)\n",
    "plt.xlabel('Weeks')\n",
    "plt.ylabel('Percentage')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4. Creating the Subreddit Social Network"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In our study, we constructed the subreddit social networks by creating links between users that replied to other users’ posts. In this section, we will present the code which was used to create the subreddits' underlying social networks. As an example, we will use the [Datasets subreddit's](https://www.reddit.com/r/datasets/) social network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+---------------------+----------------+---------------------+\n",
      "|       mindate       |      v_id      |       maxdate       |\n",
      "+---------------------+----------------+---------------------+\n",
      "| 2010-04-05 08:18:54 |    voltagex    | 2015-09-27 04:06:28 |\n",
      "| 2010-04-05 08:50:31 |      qwak      | 2010-04-09 08:37:35 |\n",
      "| 2010-04-05 14:13:55 |      brey      | 2010-04-05 14:13:55 |\n",
      "| 2010-04-05 14:44:42 | actionscripted | 2013-12-01 06:50:26 |\n",
      "| 2010-04-05 15:00:51 |     bcain      | 2012-11-14 17:57:45 |\n",
      "| 2010-04-05 15:57:46 |    reconbot    | 2010-04-05 15:57:46 |\n",
      "| 2010-04-05 19:26:25 |      jc4p      | 2010-04-06 01:05:28 |\n",
      "| 2010-04-05 22:27:12 |    Orborde     | 2010-04-05 22:27:12 |\n",
      "| 2010-04-05 23:57:52 |     dmwit      | 2010-04-05 23:57:52 |\n",
      "| 2010-04-06 00:11:33 |   alphabeat    | 2011-09-15 02:22:17 |\n",
      "+---------------------+----------------+---------------------+\n",
      "[4047 rows x 3 columns]\n",
      "\n",
      "+---------------------+----------+----------+\n",
      "|       datetime      |  src_id  |  dst_id  |\n",
      "+---------------------+----------+----------+\n",
      "| 2010-04-05 15:00:51 |  bcain   | voltagex |\n",
      "| 2010-04-05 23:57:52 |  dmwit   | Orborde  |\n",
      "| 2010-04-06 00:28:06 | voltagex |   jc4p   |\n",
      "| 2010-04-06 01:05:28 |   jc4p   | voltagex |\n",
      "| 2010-04-06 02:23:23 | voltagex |   jc4p   |\n",
      "| 2010-04-07 02:49:08 | voltagex | defrost  |\n",
      "| 2010-04-07 03:44:49 | defrost  | voltagex |\n",
      "| 2010-04-07 06:34:23 | voltagex | defrost  |\n",
      "| 2010-04-08 21:59:55 | voltagex | Orborde  |\n",
      "| 2010-04-09 00:40:58 | deserted |  tibbon  |\n",
      "+---------------------+----------+----------+\n",
      "[4811 rows x 3 columns]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "def get_subreddit_vertices_timeseries(subreddit_sf):\n",
    "    \"\"\"\n",
    "    Creates a vertices Timeseries object\n",
    "    :return: TimeSeries with the join time of each user to each subreddit\n",
    "     :rtype: gl.TimeSeries\n",
    "    \"\"\"\n",
    "    sf =  subreddit_sf.groupby(\"author\", {'mindate': agg.MIN(\"created_utc\"),\n",
    "                                         'maxdate': agg.MAX(\"created_utc\")})\n",
    "    sf['mindate'] = sf['mindate'].apply(lambda timestamp: datetime.fromtimestamp(timestamp))\n",
    "    sf['maxdate'] = sf['maxdate'].apply(lambda timestamp: datetime.fromtimestamp(timestamp))\n",
    "    sf.rename({\"author\": \"v_id\"})\n",
    "    return gl.TimeSeries(sf, index='mindate')\n",
    "\n",
    "\n",
    "def get_subreddit_interactions_timeseries(subreddit_sf):\n",
    "    \"\"\"\n",
    "    Creates subreddits interactions TimeSeries. Interaction exists between two subreddit users if user A posted a comment\n",
    "     and user B replied to A's comment\n",
    "    :return: TimeSeries with the subreddit interactions\n",
    "    :rtype: gl.TimeSeries\n",
    "    \"\"\"\n",
    "    subreddit_sf['parent_name'] = subreddit_sf[\"parent_id\"]\n",
    "    subreddit_sf['parent_kind'] = subreddit_sf['parent_id'].apply(lambda i: i.split(\"_\")[0] if \"_\" in i and i.startswith(\"t\") else None)\n",
    "    subreddit_sf['parent_id'] = subreddit_sf['parent_id'].apply(lambda i: i.split(\"_\")[1] if \"_\" in i and i.startswith(\"t\") else None)\n",
    "\n",
    "    sf = subreddit_sf[subreddit_sf['parent_kind'] == 't1'] # only reply to comments counts\n",
    "    sf = sf['author', \"created_utc\", \"id\", \"parent_id\", \"link_id\"]\n",
    "    sf = sf.join(subreddit_sf, on={\"parent_id\": \"id\"})\n",
    "    sf['datetime'] = sf['created_utc'].apply(lambda timestamp: datetime.fromtimestamp(timestamp))\n",
    "    sf.rename({'author': 'src_id', 'author.1': 'dst_id'})\n",
    "    sf = sf['src_id', 'dst_id', 'datetime']\n",
    "    return gl.TimeSeries(sf, index='datetime')\n",
    "\n",
    "def create_sgraph(v_ts, i_ts):\n",
    "    \"\"\"\n",
    "    Creates an SGraph object from the vertices and interaction TimeSeries objects\n",
    "    :param v_ts: vertices TimeSeries\n",
    "    :param i_ts: interactions TimeSeries\n",
    "    :return: SGraph with the input data\n",
    "    \"\"\"\n",
    "    edges = i_ts.to_sframe().groupby(['src_id', \"dst_id\"], operations={'weight': agg.COUNT(),\n",
    "                                                                     'mindate': agg.MIN('datetime'),\n",
    "                                                                     'maxdate': agg.MAX('datetime')})\n",
    "\n",
    "    g = gl.SGraph(vertices=v_ts.to_sframe(), edges=edges, vid_field=\"v_id\", src_field=\"src_id\", dst_field=\"dst_id\")\n",
    "    return g\n",
    "\n",
    "\n",
    "datasets_sf = sf[sf['subreddit'] =='datasets']\n",
    "datasets_sf.__materialize__()\n",
    "datasets_sf[\"created_utc\"] = datasets_sf[\"created_utc\"].astype(int)\n",
    "vertices = get_subreddit_vertices_timeseries(datasets_sf)\n",
    "interactions = get_subreddit_interactions_timeseries(datasets_sf)\n",
    "vertices.print_rows(10)\n",
    "interactions.print_rows(10)\n",
    "g = create_sgraph(vertices,interactions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We created an [SGraph object](https://turi.com/products/create/docs/generated/graphlab.SGraph.html) from the SFrame. Let's visualize the constructed social network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'num_edges': 3935, 'num_vertices': 4047}"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This non-commercial license of GraphLab Create for academic use is assigned.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[INFO] graphlab.cython.cy_server: GraphLab Create v1.10.1 started. Logging: /tmp/graphlab_server_1487650195.log\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import logging\n",
    "import bz2\n",
    "from datetime import datetime\n",
    "import graphlab as gl\n",
    "import graphlab.aggregate as agg\n",
    "import fnmatch\n",
    "\n",
    "#gl.canvas.set_target('ipynb')\n",
    "gl.set_runtime_config('GRAPHLAB_CACHE_FILE_LOCATIONS', '/data/tmp')\n",
    "gl.set_runtime_config('GRAPHLAB_DEFAULT_NUM_GRAPH_LAMBDA_WORKERS', 128)\n",
    "gl.set_runtime_config('GRAPHLAB_DEFAULT_NUM_PYLAMBDA_WORKERS', 128)\n",
    "\n",
    "\n",
    "basedir = \"/data/reddit/raw\" # Replace this with the directory which you downloaded the file into\n",
    "sframes_dir = \"/data/reddit/sframes/\" # Replace this with the directory you want to save the SFrame to\n",
    "tmp_dir =  \"/data/tmp\" # Replace this with the directory you want to save the SFrame to\n",
    "join_sframe_path = sframes_dir + os.path.sep + \"join_all.sframe\" # Where to save the join large SFrame object\n",
    "sf = gl.load_sframe(\"/data/reddit_data_no_txt_without_bots_and_deleted_authors.sframe\")\n",
    "subreddit_users = gl.load_sframe(\"/data/subreddits_users.sframe\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can use GraphLab's [analytics toolkit](https://turi.com/products/create/docs/graphlab.toolkits.graph_analytics.html) to calculate various topological properties, such as the degree distribution and the graph's number of triangles. We hope to elaborate on this in a future tutorial. For now, let's use [Networkx package](https://networkx.github.io/) to draw this subreddit's social network."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import networkx as nx\n",
    "def sgraph2nxgraph(sgraph):\n",
    "    \"\"\" Converts a directed sgraph object into networkx object\n",
    "    :param sgraph: GraphLab SGraph object\n",
    "    :return: Networkx Directed Graph object\n",
    "    \"\"\"\n",
    "    nx_g = nx.DiGraph()\n",
    "    vertices = list(sgraph.get_vertices()['__id'])\n",
    "    edges = [(e['__src_id'], e['__dst_id']) for e in sgraph.get_edges()]\n",
    "    nx_g.add_nodes_from(vertices)\n",
    "    nx_g.add_edges_from(edges)\n",
    "    return nx_g\n",
    "nx_g = sgraph2nxgraph(g)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's draw a subgraph of the subreddit                "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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973/XHZ+cnJzM9OnTKVKkCBUrVmTRokX3fEKP68UpXt0yvcSlYDAYrilW//vf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\ndAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1d8585ff90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import networkx as nx\n",
    "import random\n",
    "def draw_graph(g,layout_func=nx.spring_layout):\n",
    "    pos = layout_func(g)\n",
    "    d = nx.degree(g)\n",
    "    n_sizes = [v * 25 +5 for v in d.values()]\n",
    "    nx.draw(g, nodelist=d.keys(), node_size=n_sizes, node_color='blue')\n",
    "\n",
    "# Selecting only sample of vertices with degree greater than 0\n",
    "d = nx.degree(nx_g)    \n",
    "v_list = [v for v in d.keys() if d[v] >0]\n",
    "h = nx_g.subgraph(v_list[:500])\n",
    "draw_graph(h)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "## 5. Where to Go from Here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The social network dataset created as a result of our study opens the door for new and exciting research opportunities. This dataset can help not only to better understand the social structure of the Reddit community in particular, but also to understand how social networks and online communities evolve over time. Moreover, this corpus can be used as a ground-truth dataset for many studies in the field of social networks. Some examples of what can be done with this corpus are:\n",
    "* Understanding topological factors that may help a post to go viral.\n",
    "* Helping to better understand diffusion models and also assisting in validating diffusion models using real-world data.\n",
    "* Using this dataset as an excellent ground-truth dataset for evaluating entity-matching algorithms, based on our observation that many redditors are members in several subreddits.\n",
    "* Helping understand the connection between content and social networks; for instance, this dataset can provide insight on what type of content makes users more likely to interact with each other.\n",
    "\n",
    "We would love to hear other ideas on what possible work can be done with our provided datasets."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 6. Further Reading"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Further reading material:\n",
    "* [I have every publicly available Reddit comment for research ~ 1.7 billion comments @ 250 GB compressed. Any interest in this?](https://www.reddit.com/r/datasets/comments/3bxlg7/i_have_every_publicly_available_reddit_comment/)\n",
    "* [Navigating the massive world of Reddit: using backbone networks to map user interests in social media](https://peerj.com/articles/cs-4/)\n",
    "* [Don't feed the troll: Shutting down debate about community expectations on Reddit.com](http://firstmonday.org/ojs/index.php/fm/article/viewArticle/3498/3029)\n",
    "* [GraphLab Create User Guide](https://turi.com/learn/userguide/)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
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 },
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}