kylemcdonald/Search SMAT Data.ipynb

## Search SMAT Data.ipynb
{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "several-parliament",
   "metadata": {},
   "source": [
    "Using the data from [A Large Open Dataset from the Parler Social Network](https://zenodo.org/record/4442460#.YB44y49KhhF) downloaded to `data/smat/raw`.\n",
    "\n",
    "> Max Aliapoulios, Emmi Bevensee, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, Gianluca Stringhini, & Savvas Zannettou. (2021). A Large Open Dataset from the Parler Social Network (Version 1) \\[Data set\\]. Zenodo. http://doi.org/10.5281/zenodo.4442460"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "recreational-coordinate",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "\n",
    "import os\n",
    "from utils.progress import progress_parallel\n",
    "from utils.list_files import list_files, get_stem\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "import pytz\n",
    "from scipy.ndimage import gaussian_filter1d as gaussian\n",
    "\n",
    "input_directory = 'data/smat/raw'\n",
    "output_directory = 'data/smat/filtered'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "broken-trunk",
   "metadata": {},
   "source": [
    "Here we parse all the .ndjson files to pull out the posts from 2021, and dump a subset of the metadata (id, username, createdAt, body) to a .json file for each. This can take a while, up to 20 minutes. If you have more RAM, increase the number of processes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "sustainable-county",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "167 0:00:00 11428.25/s\n"
     ]
    }
   ],
   "source": [
    "def load_ndjson(fn):\n",
    "    with open(fn) as f:\n",
    "        raw = f.read()\n",
    "    text = '[' + ','.join(raw.splitlines()) + ']'\n",
    "    return json.loads(text)\n",
    "\n",
    "def extract(e):\n",
    "    try:\n",
    "        if len(e['body']) == 0: # only non-empty posts\n",
    "            return None\n",
    "        if e['createdAt'][3] != '1': # only 2021\n",
    "            return None\n",
    "        return e['id'], e['username'], e['createdAt'], e['body']\n",
    "    except KeyError:\n",
    "        return None\n",
    "\n",
    "def job(fn):\n",
    "    out_fn = os.path.join(output_directory, get_stem(fn) + '.json')\n",
    "    if os.path.exists(out_fn):\n",
    "        return\n",
    "    posts = load_ndjson(fn)\n",
    "    extracted = list(filter(None, map(extract, posts)))\n",
    "    with open(out_fn, 'w') as f:\n",
    "        json.dump(extracted, f)\n",
    "\n",
    "fns = list(list_files(input_directory))\n",
    "os.makedirs(output_directory, exist_ok=True)\n",
    "_=progress_parallel(job, fns, processes=6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dietary-romance",
   "metadata": {},
   "source": [
    "Load all the .json files from the `data/smat/filtered` folder. This should take around 10-15 seconds."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "historical-address",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "167 0:00:11 15.47/s\n"
     ]
    }
   ],
   "source": [
    "def job(fn):\n",
    "    with open(fn) as f:\n",
    "        return json.load(f)\n",
    "\n",
    "posts = progress_parallel(job, list_files(output_directory))\n",
    "\n",
    "flatten = lambda t: [item for sublist in t for item in sublist]\n",
    "posts = flatten(posts)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "governing-superintendent",
   "metadata": {},
   "source": [
    "Pull out the posts that are between our start and end times (5am on the 6th, to 5am on the 7th). This takes around 6 minutes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "id": "coral-fleece",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5566491 0:07:59 11631.45/s\n"
     ]
    }
   ],
   "source": [
    "est = pytz.timezone('US/Eastern')\n",
    "utc = pytz.timezone('UTC')\n",
    "\n",
    "start_time = est.localize(datetime.datetime(2021,1,5,5))\n",
    "end_time = est.localize(datetime.datetime(2021,1,8,5))\n",
    "\n",
    "def job(post):\n",
    "    post_id, username, created_at, body = post\n",
    "    dt = datetime.datetime.strptime(created_at, '%Y%m%d%H%M%S')\n",
    "    dt = dt.replace(tzinfo=utc).astimezone(est)\n",
    "    if dt > start_time and dt < end_time:\n",
    "        body = body.lower()\n",
    "        return post_id, username, dt, body\n",
    "    \n",
    "posts_6th = progress_parallel(job, posts)\n",
    "posts_6th = list(filter(None, posts_6th))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "authentic-aruba",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some code for saving and restoring previous work from a pickle file\n",
    "\n",
    "# import pickle\n",
    "# with open('data/smat/posts_6th.pkl', 'wb') as f:\n",
    "#     pickle.dump(posts_6th, f)\n",
    "\n",
    "# with open('data/smat/posts_6th.pkl', 'rb') as f:\n",
    "#     posts_6th = pickle.load(f)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "greatest-configuration",
   "metadata": {},
   "source": [
    "Pull out all the timestamps from all the posts on the 6th."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "id": "adjacent-fault",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_times = [e[2] for e in posts_6th]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "vietnamese-monkey",
   "metadata": {},
   "source": [
    "Pull out all the timestamps for posts on the 6th that mention a term (\"traitor\")."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 315,
   "id": "olive-description",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2314638 0:03:19 11654.73/s\n"
     ]
    }
   ],
   "source": [
    "term = 'civil war'\n",
    "\n",
    "def job(post):\n",
    "    post_id, username, dt, body = post\n",
    "    if term in body:\n",
    "        return dt\n",
    "    else:\n",
    "        return None\n",
    "        \n",
    "search_times = progress_parallel(job, posts_6th)\n",
    "search_times = list(filter(None, search_times))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "id": "decimal-unknown",
   "metadata": {},
   "outputs": [],
   "source": [
    "# some code for exporting matching posts to a .csv file\n",
    "\n",
    "# def job(post):\n",
    "#     post_id, username, dt, body, tokens = post\n",
    "#     if term in body:\n",
    "#         return dt, post_id, username, body\n",
    "#     else:\n",
    "#         return None\n",
    "        \n",
    "# matching = progress_parallel(job, posts_6th)\n",
    "# matching = list(filter(None, matching))\n",
    "# matching.sort()\n",
    "\n",
    "# import pandas as pd\n",
    "# df = pd.DataFrame(matching, columns = ['Time', 'Post ID', 'Username', 'Text'])\n",
    "# df.to_csv('traitor.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "assumed-headquarters",
   "metadata": {},
   "source": [
    "Convert a list of times to binned per-minute totals. We do this for all the results, and also for the search results specifically."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 317,
   "id": "approximate-congress",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "\n",
    "resolution = datetime.timedelta(minutes=1)\n",
    "\n",
    "def times_to_minute_totals(times, start_time, end_time):\n",
    "    times.sort()\n",
    "    cur = start_time.replace(second=0)\n",
    "    i = 0\n",
    "    totals = []\n",
    "    n = len(times)\n",
    "    while cur <= end_time:\n",
    "        next_time = cur + resolution\n",
    "        total = 0\n",
    "        while True:\n",
    "            if i == n:\n",
    "                break\n",
    "            time = times[i]\n",
    "            if time < next_time:\n",
    "                total += 1\n",
    "                i += 1\n",
    "            else:\n",
    "                break\n",
    "        totals.append(total)\n",
    "        cur = next_time\n",
    "    return np.asarray(totals, dtype=float)\n",
    "\n",
    "search_minutes = times_to_minute_totals(search_times, start_time, end_time)\n",
    "all_minutes = times_to_minute_totals(all_times, start_time, end_time)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "editorial-tucson",
   "metadata": {},
   "source": [
    "Helper function for generating a list of timestamps between a start and end time, in 1-minute steps."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 318,
   "id": "experimental-newsletter",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_minutes(start_time, end_time):\n",
    "    minutes = []\n",
    "    cur = start_time.replace(second=0, microsecond=0)\n",
    "    while cur <= end_time:\n",
    "        minutes.append(cur)\n",
    "        cur += resolution\n",
    "    return minutes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "alpha-financing",
   "metadata": {},
   "source": [
    "We apply a gaussian blur with a 5-minute sigma to account for some variability in the data. Parler was down around 4-7pm, which means most of that time period is not useful."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "id": "inside-speed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 263,
       "width": 721
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sigma = 10#0.1\n",
    "spacing = 240\n",
    "\n",
    "plt.figure(figsize=(12,4), facecolor='white')\n",
    "blurred_search = gaussian(search_minutes, sigma)\n",
    "blurred_all = gaussian(all_minutes, sigma)\n",
    "\n",
    "events = {\n",
    "    'Speech starts': est.localize(datetime.datetime(2021,1,6,12,0)),\n",
    "    'Pence letter': est.localize(datetime.datetime(2021,1,6,13,0)),\n",
    "    'Speech ends': est.localize(datetime.datetime(2021,1,6,13,10))\n",
    "}\n",
    "\n",
    "minutes = get_minutes(start_time, end_time)\n",
    "\n",
    "# plt.plot(minutes, blurred_search, color='black', lw=0.5, label=term)\n",
    "# plt.plot(minutes, search_minutes, color='black', lw=0.5)\n",
    "plt.plot(minutes, 100 * blurred_search / blurred_all, color='black', lw=0.5, label=term)\n",
    "\n",
    "for e in ['Speech ends']:\n",
    "    dt = events[e]\n",
    "    plt.axvline(dt, lw=0.5)\n",
    "    plt.text(dt, 0.1, e, rotation=90)\n",
    "\n",
    "# plt.legend(loc='upper left')\n",
    "# plt.twinx()\n",
    "# plt.plot(minutes, search_minutes, color='red', lw=0.5, label='all')\n",
    "# plt.legend(loc='lower right')\n",
    "\n",
    "# plt.plot(minutes, blurred_all, color='black', lw=0.5)\n",
    "plt.xlim(start_time, end_time)\n",
    "plt.xticks(minutes[::spacing], [e.time().isoformat()[:-3] for e in minutes[::spacing]])#, rotation=90)\n",
    "\n",
    "# plt.title(f'2021-01-06 Parler posts per minute mentioning: {term} (σ={sigma})')\n",
    "\n",
    "plt.title(f'2021-01-05 5am to 2021-01-08 5am Percent of Parler posts mentioning: {term} (σ={sigma})')\n",
    "plt.ylim(0)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "mounted-rendering",
   "metadata": {},
   "source": [
    "Check which terms were more common after Trump's speech began compared to before."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "sunset-anderson",
   "metadata": {},
   "outputs": [],
   "source": [
    "from collections import Counter\n",
    "\n",
    "range_start = est.localize(datetime.datetime(2021,1,6,5))\n",
    "pivot = est.localize(datetime.datetime(2021,1,6,10))\n",
    "range_end = est.localize(datetime.datetime(2021,1,6,14))\n",
    "\n",
    "before = []\n",
    "after = []\n",
    "for post in posts_6th:\n",
    "    post_id, username, dt, body, tokens = post\n",
    "    if dt < range_start or dt > range_end:\n",
    "        continue\n",
    "    if dt < pivot:\n",
    "        before.extend(list(tokens))\n",
    "    else:\n",
    "        after.extend(list(tokens))\n",
    "        \n",
    "before_total = len(before)\n",
    "before_freqs = dict([(w, c/before_total) for w,c in Counter(before).items()])\n",
    "\n",
    "after_total = len(after)\n",
    "after_freqs = dict([(w, c/after_total) for w,c in Counter(after).items()])\n",
    "\n",
    "both = set(before) & set(after)\n",
    "all_words = Counter(before + after)\n",
    "\n",
    "after_ratios = []\n",
    "for word in both:\n",
    "    count = all_words[word]\n",
    "    if count < 500:\n",
    "        continue\n",
    "    ratio = after_freqs[word] / before_freqs[word]\n",
    "    after_ratios.append((ratio, word, count))\n",
    "after_ratios.sort()\n",
    "\n",
    "after_ratios[-20:]"
   ]
  }
 ],
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