Gensim Word2Vec Play.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
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   "outputs": [
    {
     "ename": "ImportError",
     "evalue": "No module named 'plotly'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mImportError\u001b[0m                               Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-1-98943ee695ea>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      6\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mnltk\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mword_tokenize\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      7\u001b[0m \u001b[1;32mfrom\u001b[0m \u001b[0mnltk\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcorpus\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mstopwords\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 8\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplotly\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mpy\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      9\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mgraph_objs\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mgo\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     10\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mplotly\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtools\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mtls\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mImportError\u001b[0m: No module named 'plotly'"
     ]
    }
   ],
   "source": [
    "from gensim.models.word2vec import Word2Vec as w2\n",
    "from gensim import corpora, models, similarities\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "import seaborn\n",
    "from nltk import word_tokenize\n",
    "from nltk.corpus import stopwords\n",
    "import plotly.plotly as py\n",
    "import plotly.graph_objs as go\n",
    "import plotly.tools as tls\n",
    "import numpy as np\n",
    "import sklearn as sc\n",
    "import os\n",
    "import json\n",
    "\n",
    "% matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data_dir = '/Users/christopherallison/Documents/Coding/Data'\n",
    "home_dir = '/Users/christopherallison/.virtualenvs/py_twi/streaming_results'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "model = w2.load_word2vec_format(os.path.join(data_dir, 'GoogleNews-vectors-negative300.bin'), binary=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('kings', 0.5055657625198364),\n",
       " ('god', 0.4728158414363861),\n",
       " ('gods', 0.46230649948120117),\n",
       " ('deity', 0.44759321212768555),\n",
       " ('Almighty', 0.42097359895706177)]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.most_similar(positive=['king', 'man', 'wise'], negative=['old'], topn=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[('eat', 0.46837371587753296),\n",
       " ('nutritious_wholesome', 0.46666663885116577),\n",
       " ('foods', 0.45825499296188354),\n",
       " ('peopleand', 0.4524109959602356),\n",
       " ('eat_unhealthily', 0.4494132995605469)]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_text = \"invest people food\".split()\n",
    "\n",
    "model.most_similar(positive=test_text, negative=['money'], topn=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def load_tweets(target):\n",
    "    # Output list of tweets\n",
    "    tweets = []\n",
    "\n",
    "    with open(os.path.join(home_dir, target)) as f:\n",
    "        for data in f:\n",
    "\n",
    "            result = json.loads(data)\n",
    "            \n",
    "            try:\n",
    "                tweets.append(result['text'])\n",
    "            except KeyError:\n",
    "                continue\n",
    "    \n",
    "    return tweets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def process_tweets(tweets):\n",
    "    # Output processed list of tweets\n",
    "    # removed - if word not in stopwords.words('english') and word not in stopwords.words('french')\n",
    "\n",
    "    texts = [[word for word in tweet.lower().split()] for tweet in tweets]\n",
    "    \n",
    "    # Remove words that only occur once\n",
    "    from collections import defaultdict\n",
    "    frequency = defaultdict(int)\n",
    "    for text in texts:\n",
    "        for token in text:\n",
    "            frequency[token] += 1\n",
    "\n",
    "    texts = [[token for token in text] for text in texts]\n",
    "\n",
    "    from pprint import pprint\n",
    "    #pprint(texts)\n",
    "    \n",
    "    return texts\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Graph sentiment across Pleasure/Displeasure and Active/Passive as per the Russel and Pratt affect grid\n",
    "\n",
    "http://richardcoyne.com/2013/10/05/absence-of-melancholy/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def analyze_sentiment(texts):\n",
    "    # Output dictionary of tweets and sentiment scores for pleasure and activity\n",
    "    \n",
    "    tweet_sentiments = {}\n",
    "\n",
    "    for i, text in enumerate(texts):\n",
    "        pleasure = 0\n",
    "        displeasure = 0\n",
    "        active = 0\n",
    "        passive = 0\n",
    "        for word in text:\n",
    "            try:\n",
    "                pleasure += model.similarity('pleasure', word)\n",
    "                displeasure += model.similarity('displeasure', word)\n",
    "                active += model.similarity('active', word)\n",
    "                passive += model.similarity('passive', word)\n",
    "            except KeyError:\n",
    "                continue\n",
    "                \n",
    "        tweet_sentiments[i] = {'text':\" \".join(text), 'pleasure':pleasure - displeasure,\n",
    "                           'active':active - passive}\n",
    "        #print(\"Tweet {} Sentiment: pleasure {} active {}\".format(i, pleasure - displeasure, active - passive))\n",
    "\n",
    "    return tweet_sentiments"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def prepare_coords(tweet_sentiments):\n",
    "    # Output list of coordinates in tuple (x, y)\n",
    "    coordinates = []\n",
    "\n",
    "    for tweet in tweet_sentiments:\n",
    "        x = tweet_sentiments[tweet]['pleasure'] - tweet_sentiments[tweet]['displeasure']\n",
    "        y = tweet_sentiments[tweet]['active'] - tweet_sentiments[tweet]['passive']\n",
    "\n",
    "        coordinates.append((x, y))\n",
    "        \n",
    "    return coordinates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "def graph_tweets(tweet_sentiments, title):\n",
    "    # Accepts dictionary of tweet sentiments & title, outputs graph and stats\n",
    "    \n",
    "    anger = 0\n",
    "    excitement = 0\n",
    "    content = 0\n",
    "    sorrow = 0\n",
    "    \n",
    "    pleasure_sum = 0.0\n",
    "    active_sum = 0.0\n",
    "    \n",
    "    plt.figure(figsize=(20,10))\n",
    "\n",
    "    for tweet in tweet_sentiments:\n",
    "        x = tweet_sentiments[tweet]['pleasure']\n",
    "        y = tweet_sentiments[tweet]['active']\n",
    "        \n",
    "        pleasure_sum += x\n",
    "        active_sum += y\n",
    "\n",
    "        if x > 0 and y > 0:\n",
    "            color = 'b'\n",
    "            excitement += 1\n",
    "        elif x < 0 and y > 0:\n",
    "            color = 'r'\n",
    "            anger += 1\n",
    "        elif x > 0 and y < 0:\n",
    "            color = 'g'\n",
    "            content += 1\n",
    "        else:\n",
    "            color = 'y'\n",
    "            sorrow += 1\n",
    "\n",
    "        plt.plot(x, y, marker='o', markersize=8, color=color)\n",
    "    \n",
    "    plt.xlabel('pleasure')\n",
    "    plt.ylabel('activity')\n",
    "    plt.title('Sentiment Analysis of Tweets: {}'.format(title))\n",
    "    \n",
    "    plt.grid(True)\n",
    "    blue_patch = mpatches.Patch(color='blue', label=\"Excitement\")\n",
    "    red_patch = mpatches.Patch(color='red', label='Anger')\n",
    "    green_patch = mpatches.Patch(color='green', label='Content')\n",
    "    yellow_patch = mpatches.Patch(color='yellow', label='Sorrow')\n",
    "    \n",
    "    plt.axvline(0)\n",
    "    plt.axhline(0)\n",
    "\n",
    "    first_legend = plt.legend(handles=[blue_patch], loc=1)\n",
    "    second_legend = plt.legend(handles=[red_patch], loc=2)\n",
    "    third_legend = plt.legend(handles=[green_patch], loc=4)\n",
    "    fourth_legend = plt.legend(handles=[yellow_patch], loc=3)\n",
    "    \n",
    "    ax = plt.gca().add_artist(first_legend)\n",
    "    ax = plt.gca().add_artist(second_legend)\n",
    "    ax = plt.gca().add_artist(third_legend)\n",
    "    \n",
    "    print(\"Mood Breakdown for {}\".format(title))\n",
    "    print(\"Total Tweets: {}\".format(len(tweet_sentiments)))\n",
    "    print('Average Pleasure: {0:.2f}'.format(pleasure_sum / len(tweet_sentiments)))\n",
    "    print('Average Active: {0:.2f}'.format(active_sum / len(tweet_sentiments)))\n",
    "    print(\"*****\")\n",
    "    print('Excitement: {0:.2f}%'.format((excitement / len(tweet_sentiments))*100))\n",
    "    print('Content: {0:.2f}%'.format((content / len(tweet_sentiments))*100))\n",
    "    print('Anger: {0:.2f}%'.format((anger / len(tweet_sentiments))*100))\n",
    "    print('Sorrow: {0:.2f}%\\n'.format((sorrow / len(tweet_sentiments))*100))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Plotly scatter\n",
    "def plotly_graph_tweets(tweet_sentiments, title):\n",
    "    \n",
    "    x_coords = []\n",
    "    y_coords = []\n",
    "    texts = []\n",
    "    color = []\n",
    "\n",
    "    for tweet in tweet_sentiments:\n",
    "        x = tweet_sentiments[tweet]['pleasure']\n",
    "        y = tweet_sentiments[tweet]['active']\n",
    "            \n",
    "        x_coords.append(x)\n",
    "        y_coords.append(y)\n",
    "        texts.append(tweet_sentiments[tweet]['text'])\n",
    "        \n",
    "        if x > 0 and y > 0:\n",
    "            color.append('blue')\n",
    "        elif x < 0 and y > 0:\n",
    "            color.append('red')\n",
    "        elif x > 0 and y < 0:\n",
    "            color.append('green')\n",
    "        else:\n",
    "            color.append('yellow')\n",
    "\n",
    "    trace0 = go.Scatter(\n",
    "        x=x_coords,\n",
    "        y=y_coords,\n",
    "        mode='markers',\n",
    "        name=title,\n",
    "        text=texts,\n",
    "        marker=dict(\n",
    "            size=8,\n",
    "            color=color,\n",
    "        )\n",
    "    )\n",
    "\n",
    "\n",
    "    data = [trace0]\n",
    "    layout = go.Layout(\n",
    "\n",
    "        xaxis=dict(\n",
    "            range=[-2.0, 2.0],\n",
    "            autorange=False,\n",
    "        ),\n",
    "\n",
    "        yaxis=dict(\n",
    "            range=[-2.0, 2.0],\n",
    "            autorange=False,\n",
    "        ),\n",
    "    )\n",
    "    fig = go.Figure(data=data, layout=layout)\n",
    "    py.plot(fig, filename='{} Plot'.format(title))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![Graph](http://rcoyne99.files.wordpress.com/2013/10/screen-shot-2013-10-05-at-15-37-13.png?w=800&h=730)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "trudeau_tweets = load_tweets('trudeau_stream.json')\n",
    "processed_trudeau_tweets = process_tweets(trudeau_tweets)\n",
    "sentiment_trudeau = analyze_sentiment(processed_trudeau_tweets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "harper_tweets = load_tweets('harper_stream.json')\n",
    "processed_harper_tweets = process_tweets(harper_tweets)\n",
    "sentiment_harper = analyze_sentiment(processed_harper_tweets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mood Breakdown for Trudeau\n",
      "Total Tweets: 107813\n",
      "Average Pleasure: 5.75\n",
      "Average Active: -11.38\n",
      "*****\n",
      "Excitement: 12.45%\n",
      "Content: 44.50%\n",
      "Anger: 11.17%\n",
      "Sorrow: 31.88%\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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Hboei/AKPPJLGvHkJjI39Gm9+89vwJ3/yp/jKV76IyclJrFq1OrRAE4NMIdq69dvYsOEq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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2dcf19eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_tweets(sentiment_trudeau, 'Trudeau')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "plotly_graph_tweets(sentiment_trudeau, 'Trudeau')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mood Breakdown for Harper\n",
      "Total Tweets: 110067\n",
      "Average Pleasure: 0.03\n",
      "Average Active: -0.14\n",
      "*****\n",
      "Excitement: 10.01%\n",
      "Content: 43.35%\n",
      "Anger: 13.74%\n",
      "Sorrow: 32.91%\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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UmzffyYED+wmF/o3Zs2f7/AhFpFqEQo2e2xQqiYiIiIhkb8eO7XzoQ1eNf/3qV/8FH//4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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2c2ce2dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_tweets(sentiment_harper, \"Harper\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "mulcair_tweets = load_tweets('mulcair_stream.json')\n",
    "processed_mulcair_tweets = process_tweets(mulcair_tweets)\n",
    "sentiment_mulcair = analyze_sentiment(processed_mulcair_tweets)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mood Breakdown for mulcair\n",
      "Total Tweets: 1024\n",
      "Average Pleasure: -0.03\n",
      "Average Active: -0.15\n",
      "*****\n",
      "Excitement: 9.18%\n",
      "Content: 31.84%\n",
      "Anger: 18.16%\n",
      "Sorrow: 40.82%\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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ESveDtlfAMX++XZLfeMZ4FFlWnFJvH11LCPQAVKtS91bKFj2ZgCpE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      "text/plain": [
       "<matplotlib.figure.Figure at 0x2f0c6ed30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "graph_tweets(sentiment_mulcair, \"mulcair\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "plotly_graph_tweets(sentiment_mulcair, 'Mulcair')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mood Breakdown for Cdnpoli\n",
      "Total Tweets: 120621\n",
      "Average Pleasure: -0.02\n",
      "Average Active: -0.05\n",
      "*****\n",
      "Excitement: 15.15%\n",
      "Content: 28.58%\n",
      "Anger: 20.65%\n",
      "Sorrow: 35.61%\n",
      "\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "Traceback (most recent call last):\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/ipykernel/ipkernel.py\", line 175, in do_execute\n    shell.run_cell(code, store_history=store_history, silent=silent)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/interactiveshell.py\", line 2908, in run_cell\n    self.events.trigger('post_execute')\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/events.py\", line 74, in trigger\n    func(*args, **kwargs)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/ipykernel/pylab/backend_inline.py\", line 113, in flush_figures\n    return show(True)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/ipykernel/pylab/backend_inline.py\", line 36, in show\n    display(figure_manager.canvas.figure)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/display.py\", line 159, in display\n    format_dict, md_dict = format(obj, include=include, exclude=exclude)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/formatters.py\", line 175, in format\n    data = formatter(obj)\n",
      "  File \"<decorator-gen-9>\", line 2, in __call__\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/formatters.py\", line 220, in catch_format_error\n    r = method(self, *args, **kwargs)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/formatters.py\", line 337, in __call__\n    return printer(obj)\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/pylabtools.py\", line 207, in <lambda>\n    png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))\n",
      "  File \"/Users/christopherallison/anaconda/lib/python3.4/site-packages/IPython/core/pylabtools.py\", line 117, in print_figure\n    fig.canvas.print_figure(bytes_io, **kw)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/backend_bases.py\", line 2211, in print_figure\n    **kwargs)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/backends/backend_agg.py\", line 521, in print_png\n    FigureCanvasAgg.draw(self)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/backends/backend_agg.py\", line 469, in draw\n    self.figure.draw(self.renderer)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/artist.py\", line 59, in draw_wrapper\n    draw(artist, renderer, *args, **kwargs)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/figure.py\", line 1085, in draw\n    func(*args)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/artist.py\", line 59, in draw_wrapper\n    draw(artist, renderer, *args, **kwargs)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/axes/_base.py\", line 2110, in draw\n    a.draw(renderer)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/artist.py\", line 59, in draw_wrapper\n    draw(artist, renderer, *args, **kwargs)\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/lines.py\", line 686, in draw\n    gc = renderer.new_gc()\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/backend_bases.py\", line 708, in new_gc\n    return GraphicsContextBase()\n",
      "  File \"/Users/christopherallison/.virtualenvs/py_twi/lib/python3.4/site-packages/matplotlib/backend_bases.py\", line 779, in __init__\n    self._cliprect = None\n",
      "KeyboardInterrupt\n"
     ]
    }
   ],
   "source": [
    "cdnpoli_tweets = load_tweets('cdnpoli_stream.json')\n",
    "processed_cdnpoli_tweets = process_tweets(cdnpoli_tweets)\n",
    "sentiment_cdnpoli = analyze_sentiment(processed_cdnpoli_tweets)\n",
    "\n",
    "graph_tweets(sentiment_cdnpoli, \"Cdnpoli\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class MyTweets(object):\n",
    "    def __init__(self, target):\n",
    "        self.target = target\n",
    "    \n",
    "    def __iter__(self):\n",
    "        for line in open(os.path.join(home_dir, self.target)):\n",
    "            result = json.loads(line)\n",
    "            text = result['text']\n",
    "            yield dictionary.doc2bow(text.lower().split())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<__main__.MyTweets at 0x251662908>"
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<__main__.MyTweets object at 0x251662908>\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[(2, 1), (31, 1), (35, 1), (52, 1), (213, 1), (217, 1), (220, 1), (249, 1), (250, 1), (378, 1), (406, 1)]\n",
      "[(20, 1), (63, 1), (131, 1), (133, 1), (178, 1), (181, 1), (188, 1), (248, 1), (362, 1)]\n",
      "[(2, 1)]\n",
      "[(72, 1), (123, 1), (199, 1), (272, 1)]\n",
      "[(2, 1), (29, 1), (123, 1), (127, 1), (128, 1), (129, 1), (130, 1), (131, 1), (132, 1), (133, 1), (134, 1), (135, 1), (136, 1), (137, 1)]\n",
      "[(26, 1), (96, 1), (131, 1), (172, 1), (201, 1), (275, 1), (378, 1)]\n",
      "[(22, 1), (24, 1), (34, 1), (44, 1), (101, 1), (131, 1)]\n",
      "[(2, 1), (29, 1), (48, 1), (53, 1), (101, 1), (109, 1), (143, 1), (197, 1), (198, 1), (199, 1), (200, 1), (201, 1)]\n",
      "[(46, 1), (48, 1), (106, 1), (131, 1), (272, 1)]\n",
      "[(131, 1)]\n",
      "[(163, 1)]\n",
      "[(2, 1), (54, 1), (121, 1), (128, 1), (172, 1), (192, 1), (359, 1)]\n",
      "[(2, 1), (29, 1), (65, 1), (92, 1), (111, 1), (131, 1), (178, 1), (268, 1), (269, 1), (270, 1)]\n",
      "[(1, 1), (29, 1), (34, 1), (276, 1), (277, 1)]\n",
      "[(2, 1), (46, 1), (49, 1), (97, 1), (131, 1), (220, 1), (354, 1)]\n",
      "[(2, 1), (26, 1), (96, 1), (131, 1), (172, 1), (201, 1), (275, 1), (378, 1)]\n",
      "[(2, 1), (163, 1)]\n",
      "[(21, 2), (72, 1)]\n",
      "[(74, 1), (131, 1), (178, 1), (447, 1)]\n",
      "[(2, 1), (29, 1), (123, 1), (127, 1), (128, 1), (129, 1), (130, 1), (131, 1), (132, 1), (133, 1), (134, 1), (135, 1), (136, 1), (137, 1), (328, 1)]\n",
      "[(0, 1), (2, 1), (13, 1), (112, 1), (131, 1), (189, 1), (378, 1)]\n",
      "[(2, 1), (4, 1), (96, 1), (116, 1), (131, 1), (418, 1)]\n",
      "[(2, 1), (423, 1)]\n",
      "[(2, 1), (21, 1), (111, 1), (131, 1), (181, 2), (184, 1), (206, 1), (237, 1), (418, 1), (448, 1)]\n",
      "[(2, 2), (72, 1), (131, 1)]\n",
      "[(2, 1), (29, 1), (54, 1), (103, 1), (131, 1), (175, 4), (362, 1), (374, 1), (375, 1), (376, 1), (377, 2)]\n",
      "[(2, 1), (91, 1), (102, 1), (131, 1), (378, 1)]\n",
      "[(131, 1)]\n",
      "[(2, 1), (34, 1), (54, 1), (131, 1), (221, 1)]\n",
      "[(1, 1), (13, 2), (21, 1), (46, 1), (106, 2), (114, 1), (131, 1), (215, 1)]\n",
      "[(2, 1), (131, 1), (275, 1)]\n",
      "[(123, 1)]\n",
      "[(29, 1), (45, 1), (180, 1), (237, 1), (374, 1), (446, 1)]\n",
      "[(2, 1), (31, 1), (35, 1), (52, 1), (213, 1), (217, 1), (220, 1), (249, 1), (250, 1), (378, 1), (406, 1)]\n",
      "[(0, 1), (7, 1), (54, 1), (111, 1), (131, 1), (217, 1), (274, 1), (375, 1)]\n",
      "[(2, 1), (31, 1), (35, 1), (52, 1), (213, 1), (217, 1), (220, 1), (249, 1), (250, 1), (378, 1), (406, 1)]\n",
      "[(2, 1), (55, 1), (131, 2), (181, 1), (337, 1), (374, 2)]\n",
      "[(2, 1), (54, 1), (65, 1), (92, 1), (101, 1), (131, 1), (210, 1), (362, 1)]\n",
      "[(2, 1), (31, 1), (46, 1), (53, 1), (72, 1), (123, 1), (131, 1), (143, 1), (237, 1), (249, 1)]\n",
      "[(2, 1), (20, 1), (63, 1), (123, 1), (129, 1), (131, 1), (133, 1), (178, 1), (181, 1), (188, 1), (248, 1), (362, 1)]\n",
      "[(13, 1), (22, 1), (24, 1), (172, 1), (199, 1), (215, 1)]\n",
      "[(2, 1), (34, 1), (54, 1), (131, 1), (221, 1)]\n"
     ]
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def getWordVecs(text):\n",
    "    vecs = []\n",
    "    for word in text:\n",
    "        try:\n",
    "            vecs.append(model[word].reshape(1,300))\n",
    "        except KeyError:\n",
    "            continue\n",
    "    vecs = np.concatenate(vecs)\n",
    "    return np.array(vecs, dtype='float')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "tweet_text = []\n",
    "\n",
    "for line in open(os.path.join(home_dir, 'harper_stream.json')):\n",
    "    result = json.loads(line)\n",
    "    text = result['text']\n",
    "    tweet_text.append(text)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['RT @BD_CDA: @MrDash109 @___Danno Gopnik writes: \"Stephen Harper—a charmless but effective politician\". Effective? How about \"charmless but …',\n",
       " 'RT @JustinTrudeau: To stop Stephen Harper, we need you to vote. Find your advance polling location: http://t.co/RtSzoTP9cc http://t.co/GOfO…',\n",
       " 'Vote ABC https://t.co/4kXESMVXwu',\n",
       " '@1planet_People your an idiot. Harper best prime minister in last 40 yrs.  your a regressive liberal and make no sense',\n",
       " \"RT @Bollyone: Check Out @sonamakapoor @BeingSalmanKhan stunning Shoot Harper's Bazaar Bride Magazine http://t.co/rJ1nPgLD0M http://t.co/YrV…\",\n",
       " 'Sign! RT! I just signed this petition, please join me: http://t.co/z6nxm9lq5P via @leadnowca',\n",
       " \"It's positive you agree we have a surplus in 2015. Which is what matters https://t.co/JsVkTjBbB8\",\n",
       " \"RT So happy you voted! This early turnout bodes well for Canada! Can't wait to see the back of &amp; bring back our de… https://t.co/CZmUyEu6zZ\",\n",
       " \"aviateur1954Au contraire net recul avec Harper ex :l'international  Environnement, dossier F-35 @jeande1221 @piano55100 @MarioBrunet62\",\n",
       " 'RT @Vincenlair: Je pense aller voter le visage couvert de pétrole. Bah quoi, je dénonce Harper oui ou non? #elxn42',\n",
       " 'RT @trevvab: I was just wondering but has Stephen Harper started looking for a new job? I mean in this economy, the one he ruined, must be …',\n",
       " \"RT @hydroqueen: Harper brand collapses - desperate #cpc go to ads that say it's not about Harper. When you get rid of him as leader - let u…\",\n",
       " 'Protester charges at Stephen Harper during turbulent B.C. campaign rally #cdnpoli #elxn42 http://t.co/hV5LHnUbYi',\n",
       " 'roy harper is a little baby who must be protected at all costs.',\n",
       " 'RT @calgarykiaguy: Trudeau within reach of a Majority shows voting for NDP only helps Harper #cdnpoli #toronto #montreal… https://t.co/Fazx…',\n",
       " 'RT @Go4Darrell: @MinJoeOliver you and Harper have my vote!\\n\\nJust kidding.\\n\\n#RealChange\\n\\n#TeamTrudeau\\n\\n#cdnpoli',\n",
       " 'RT @almondfact: stephen harper and umi sonoda matching UR set http://t.co/YHvsGBwyL4',\n",
       " 'RT @almondfact: stephen harper and umi sonoda matching UR set http://t.co/YHvsGBwyL4',\n",
       " \"Harper is singing Canada's version of the Republican suicide ballad. Canadians R not as racist as he bargained for! https://t.co/GGa3DwI4Wo\",\n",
       " 'Racial baiting for electoral advantage. 587 Canadian academics condemn Stephen Harper’s racial hate propaganda http://t.co/orj45pXfMt',\n",
       " 'RT @JustinTrudeau: To stop Stephen Harper, we need you to vote. Find your advance polling location: http://t.co/RtSzoTP9cc http://t.co/GOfO…',\n",
       " 'RT @calling1out: Where has it gotten us @justintrudeau?  2 quarters of surpluses and strongest economy of G7.  Read a book sometime https:/…',\n",
       " 'RT @BevAzevedo: Vote strategically! Vote for the candidate that will vote out Harper.  My candidate is #Liberal #stopharper #cdnpoli @rickm…',\n",
       " 'RT @Go4Darrell: @MinJoeOliver you and Harper have my vote!\\n\\nJust kidding.\\n\\n#RealChange\\n\\n#TeamTrudeau\\n\\n#cdnpoli',\n",
       " \"RT @liberal_party: Unlike Harper's Conservatives, a Liberal government will re-engage on Canadian health care. Here are our priorities: htt…\",\n",
       " 'The Harper Government has donated $8 million of Canadian tax payers funds to the (notorious) International Republican Institute',\n",
       " \"Stephen Harper's Conservatives have been very harmful to people who are the most harmless and who mean him the least harm; marijuana users.\",\n",
       " 'RT @LisaChambers201: @Hyper_Canadian @PeggyNashNDP \"Only 35 seats more and #NDP can replace Stephen Harper\" -&gt; Is #NDP using 2011 numbers?!…',\n",
       " \"RT @clerysboy: Take my chances with Mr. Harper thank you! @pmharper Justin just doesn't have a clue, not a leader @JustinTrudeau  https://t…\",\n",
       " 'RT @ARTofHope: @acoyne Maybe Canadians finally looked in the Harper mirror and recoiled in horror at what we are becoming. #cdnpoli #elxn42…',\n",
       " \"I think selecting refugees based on religion is against our Charter. I guess Harper doesn't care what the Charter says. #cdnpoli\",\n",
       " 'Feschuk: The Stephen Harper fear index http://t.co/GLFmNJibEi via @macleansmag',\n",
       " \"RT @SheilaGunnReid: I still don't know what these people want to stop Harper from doing?\",\n",
       " 'Using FEAR! as usual. Hard to imagine any party fucking up worse then Chairman Harper and his band of thieves. https://t.co/kp4Mz2G8EB',\n",
       " 'Vote ABC https://t.co/SSNZeb0RTx',\n",
       " 'RT @jofo2005: Another nail in the coffin for Harper! #elexn42 http://t.co/wHBYBHXkWL',\n",
       " \"RT @JustinTrudeau: Harper is wasting your money on partisan ads. Sign and RT this petition if you've had enough. https://t.co/9Vr7TNnI3q\",\n",
       " 'Want a turkey to carve up? try Harper. https://t.co/M8GFkbdynt',\n",
       " 'RT @MrDash109: Harper embarrasses Canada yet again http://t.co/QK6klRszBv … Boot him out on Oct 19. Unless you like being embarrassed, anyw…',\n",
       " '@Adam_Sarson Stephen Harper is not going let him wear that at his citizenship ceremony  https://t.co/sUCLPi3AVf',\n",
       " \"RT @RDSimper: The allowance of Michael Chong's 'Reform Act' to pass is enough to kill the 'Harper is a Dictator' narrative. Haters gonna ha…\",\n",
       " \"RT @SheilaGunnReid: I still don't know what these people want to stop Harper from doing?\",\n",
       " \"RT @Takahata101: Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/zzQ3cgzyxz #elxn42\",\n",
       " \"I DON'T believe the Harper Gov do YOU?\\n\\nhttp://t.co/LVPTeONE8q\\n#cdnpoli #onpoli #qcpoli #abpoli #bcpoli #skpoli #nbpoli\",\n",
       " \"Is this Harper's world: anti-Semitism BAD Islamophobia OK\\n\\nhttp://t.co/ljVAcKXfzh\\n#cdnpoli #onpoli #qcpoli #abpoli #bcpoli\",\n",
       " 'RT @TheD_Zone: #TheDZone #SSS #WAR Round 2 (http://t.co/spq5jnKqsJ\\n\\nRT for Mason\\nFAV for Harper Creek http://t.co/vGu7CXiRz4',\n",
       " 'RT @DillionLover: Dillion Harper ia among the most dignified personalities, who carries herself in style! These photos are proof. http://t.…',\n",
       " 'RT @janfromthebruce: Trudeau has supported Harper on everything that undermines our sovereignty #TPP #CETA #C51 #FIPA #BarbaricCulturalPrac…',\n",
       " \"RT @SpeakeasyJames: Therefore PM Harper's move was a boon to Canadian democracy. A very good thing for all Canadians.  https://t.co/nfnZOqS…\",\n",
       " 'RT @KivaBay: @Veeren_Jubbal  https://t.co/2pM1TldqCt',\n",
       " \"RT @JustinTrudeau: Harper is wasting your money on partisan ads. Sign and RT this petition if you've had enough. https://t.co/9Vr7TNnI3q\",\n",
       " 'RT @Bergg69: We all know Harper  will CHEAT again in this election its why we need Everyone to VOTE! #cdnpoli https://t.co/8La796ymDQ',\n",
       " \"@sharongregson @orengendp Yeah but that's sensible thinking..not Liberal thinking.Better Trudeau&amp; Harper never used daycare?\",\n",
       " \"RT @ashcech: Stephen Harper's racist rhetoric helps inspire fellow racists. I hope all Muslim women stay safe. #elxn42 #cdnpoli\",\n",
       " 'RT @billhillier: #cbpoli #nspoli http://t.co/IzRnld7unD',\n",
       " 'RT @Vincenlair: Je pense aller voter le visage couvert de pétrole. Bah quoi, je dénonce Harper oui ou non? #elxn42',\n",
       " \"RT @EvenCool: Screw Harper's economy! How can ppl follow a corrupt, arrogant, woman hater, anti-gay, egocentric,  control freak? Vote 4 @Th…\",\n",
       " 'RT @Sue_Lib: Harper’s election ad about mentally ill father interferes with justice system: lawyers http://t.co/k2EWsjp5Ml  #cdnpoli #elxn42',\n",
       " 'me when harper gets voted out of office  https://t.co/Id3AQzq2hA',\n",
       " 'RT @QQ_ZZZ: Breaking!!\\n. @MargaretAtwood (903K following) endorsed @leadnowca \\n\\nhttps://t.co/TXo8EuSWsa',\n",
       " 'I`m gonna laugh when Harper gets re elected and all those Liberal supporters go back into their holes.....',\n",
       " 'Agreed. Her victory is a victory for all of us who love Canada. #cdnpoli https://t.co/1sZlMqRXVx',\n",
       " 'RT @JustinTrudeau: Stephen Harper’s neglect of Nutrition North has hurt our northern communities. Let’s fix it: http://t.co/xFtZcfFiir',\n",
       " \"Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/vELqahlX2g #elxn42\",\n",
       " 'Top 3 Harper protest songs: Harperman by Tony Turner https://t.co/p4fPXRVy7N',\n",
       " 'RT @ABCVeterans2015: The Harper Conservatives cuts to vets are ruthless, shameful &amp; disgrace to Canada #cdnpoli #elxn42 #onpoli #bcpoli htt…',\n",
       " 'I rather pitch to Bryce Harper than Utley/Rollins any day of the week',\n",
       " \"what Harper's divide &amp; inflame politics is doing across this country. #elxn42 #countrywewant  https://t.co/cQEz4dapij\",\n",
       " \"RT @2010redmittens: @acoyne CPC is JUST NOT ABLE to get ahead. Harper can't create racists out of honest, decent, accepting ppl of FN &amp; Can…\",\n",
       " 'RT @calgarykiaguy: Trudeau within reach of a Majority shows voting for NDP only helps Harper #cdnpoli #toronto #montreal #yvr #yyc http://t…',\n",
       " 'RT @rabbleca: The real legacy of Stephen Harper? This: http://t.co/GHc3sUL03J #elxn42 #cdnpoli http://t.co/jNIa4lYyqT',\n",
       " \"RT @2010redmittens: @acoyne CPC is JUST NOT ABLE to get ahead. Harper can't create racists out of honest, decent, accepting ppl of FN &amp; Can…\",\n",
       " 'RT @felocooo: Ella es tan hermosa https://t.co/BuqUxCRdAV',\n",
       " 'RT @jburgett34: Miss Harper has a great time tonight at @MISpeedway for Wheelin and Dealin for @MISCares! http://t.co/E1q18qWXtT',\n",
       " 'RT @Ms_Danna: And in Peterborough ON last federal election -&gt; The Harper Hillbillies.\\n\\n#elxn2015 #stopharper http://t.co/dm4ipc8hbw',\n",
       " \"RT @SalmanAddict: Behind the scenes of Sonam and Salman's hot Harper's Bazaar Bride - Sexy and single #SmashingFirstLookOfSULTAN !! 👻 http:…\",\n",
       " '#bcpoli #elxn42 RT @globalnewsto: Harper election ad targets mentally ill: lawyers http://t.co/88ZfPrJYAf http://t.co/YGEqFbp27P',\n",
       " 'the day WILL come, your electoral will make a poor decision, just like Harper.  Vote rationally..not emotional. #canada',\n",
       " '@sssmacarthur The \"Obama is petty and vindictive\" argument is a strike against him, not Harper. #KeystoneXL #Elxn42 @TNorrisYEG @BreezyXC60',\n",
       " \"RT @janewordsmith: Any oil field workers voting for Harper just know that you're voting to give Your Own Job away.\\nGood luck with that.\\nhtt…\",\n",
       " 'RCMP grab protester during a campaign event by Conservative Liar Stephen Harper in Surrey, B.C. Thursday. #cdnpoli http://t.co/JXoVcqKhpI',\n",
       " \"RT @MATUGAMATUGA: Harper is singing Canada's version of the Republican suicide ballad. Canadians R not as racist as he bargained for! https…\",\n",
       " \"RT @Bergg69: I DON'T believe the Harper Gov do YOU?\\n\\nhttp://t.co/LVPTeONE8q\\n#cdnpoli #onpoli #qcpoli #abpoli #bcpoli #skpoli #nbpoli\",\n",
       " 'RT @garfieldslogan: me when harper gets voted out of office  https://t.co/Id3AQzq2hA',\n",
       " \"RT @SheilaGunnReid: Shitter's full, Randy. Get out.  https://t.co/mZnyAeUn2n\",\n",
       " '@NatObserver @thevinetwayway @liberal_party @Raffi_RC @Garossino we can blame Harper for this....',\n",
       " 'RT @sonicfan420: Chances/The Strokes, Touch/Daft Punk, Old Souls/Jessica Harper https://t.co/KnqtMFbTn0',\n",
       " \"RT @ByeByeHarper: Dean Del Mastro isn't Stephen Harper's only friend in trouble with the law. He has 17 more #cdnpoli http://t.co/CCoWeanrgc\",\n",
       " '@Go4Darrell @2010redmittens Mr @MinJoeOliver Harper wrote to best Hockey book ever . I`m kidding too Where Kicking CPC Elections Cheats Out',\n",
       " \"RT @CdnImm: @RCIisLeaking It's probably backfiring on Harper. Read inspiring tweets at  #MuslimVoteWeekend\",\n",
       " 'RT @stephenlautens: The cycle of Harper crisis management. #cdnpoli #elxn42 http://t.co/X6ZWizAjic',\n",
       " 'RT @mybgift2014: http://t.co/lfmIg3rQyJ\\nIt is not Harper who is Deranged.....LOOK TO YOUR LEFT...do read full article \\n#Besmart #BeWise #Vo…',\n",
       " \"Right now it is looking like a Harper minority government, we need electoral reform when 70% of the population doesn't want you.\",\n",
       " 'RT @JustinTrudeau: To stop Stephen Harper, we need you to vote. Find your advance polling location: http://t.co/RtSzoTP9cc http://t.co/GOfO…',\n",
       " \"MT @janni_joy: MT @rabbleca: @brentrathgeber gives ex #CPC insider's take on #Harper #PMO sins @djclimenhaga http://t.co/a6MqeA72Di #elxn42\",\n",
       " 'RT @RCIisLeaking: RCMP grab protester during a campaign event by Conservative Liar Stephen Harper in Surrey, B.C. Thursday. #cdnpoli http:/…',\n",
       " 'Waiting for inspirational voices in Canadian political economy.http://t.co/cEDJtDgN9K #Harper #Trudeau2015 #Mulcair http://t.co/VWJfyxqSFa',\n",
       " 'RT @UncleRee1: Shocking! Talented diplomat reduced to zombie Harper cabinet minister... Harper eats your soul... #elxn42  https://t.co/cqyx…',\n",
       " 'Liza Harper sucks ... http://t.co/Q6QUcKcv1a #BigTit #Blowjob #DeepThroat #HD #sexy #porno #nsfw #tits http://t.co/5O1R9yLUfh',\n",
       " 'RT @CarolHusband: Media say ISIS is now a world power. Mulcair will appease them. Trudeau will study them. May will drink. Harper will prot…',\n",
       " \"RT @wwcawayne: #Canada while we haven't talk much about healthcare #Harper doesn't care be sure in he would Americanize it #cdnpoli https:/…\",\n",
       " '@seantasson @JustinTrudeau if Harper said 12, sleeps all hell wudda broke loose ..do not need an immature man as leader in this world',\n",
       " \"When your mom gets a book deal with Harper Collins and she's gonna be rich and famous and her dreams are coming true and uR CRYING\",\n",
       " 'Chewy peed on a Stephen Harper campaign sign #elxn41 #TMLtalk',\n",
       " \"The Harper Government Thinks We're a bunch of idiots http://t.co/jQ7KzCtHa8\",\n",
       " 'never to be seen again? #cdnpoli #C51 #C24  https://t.co/aX9qpCztaz',\n",
       " \"Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/saNxF6XpAy #elxn42\",\n",
       " 'RT @stephenlautens: The cycle of Harper crisis management. #cdnpoli #elxn42 http://t.co/X6ZWizAjic',\n",
       " 'Downgraded Credit, Degraded UN, hoodwinked TPP, $57B stolen EI, $8M given to US Repubs, 50B less trade, $150B Debt https://t.co/wUjBioGKwT',\n",
       " \"Vote CPC. Harper's plan is working. Let's stay the course https://t.co/gYYbHcbm9Y\",\n",
       " 'Harper is pure Machiavelli! He talks to us like his dog.He condescends terribly and has audacity to call himself a friend! He is an enemy.xo',\n",
       " 'RT @RCIisLeaking: RCMP grab protester during a campaign event by Conservative Liar Stephen Harper in Surrey, B.C. Thursday. #cdnpoli http:/…',\n",
       " 'y si vamos a darles quiebre Chewie Harper Elvis Tek http://t.co/oSeYqknaib',\n",
       " 'RT @Davejonesy: Strategic voters, especially in #yegcentre, read this - @randyb4yeg &amp; #LPC are the team to oust Harper.  https://t.co/PRCj4…',\n",
       " 'RT @shutupcindy: i am president of the bryce harper protection squad but why does homie gotta make my job so hard https://t.co/j7OneiZVyx',\n",
       " 'RT @AlanaBowker: What do you care? The Liberals voted with Harper on everything that mattered. @Carolyn_Bennett @_scottreid @VoteCarolyn #e…',\n",
       " 'Dumbass bitch wanna be -Harper',\n",
       " \"RT @hydroqueen: Harper brand collapses - desperate #cpc go to ads that say it's not about Harper. When you get rid of him as leader - let u…\",\n",
       " '*********** http://t.co/0Xie1Vljtk *********** Liza Harper sucks ... http://t.co/pfTkWDIphc #BigTit #Blowjob #DeepT… http://t.co/57ojZXczVF',\n",
       " 'A vote for Harper is a vote for Nickelback. http://t.co/cMg1hyzxgx',\n",
       " \"sorry lose all respect for any1 let's NDP spew this utter nonsense n mislead lesson 1 u have no seat no1 does CLEAR? https://t.co/36sB2JUQ5P\",\n",
       " \"RT @___Danno: @stephenlautens If anything should be investigated it's Harper seizing control of Imigration Canada for political purposes #c…\",\n",
       " \"RT @PaquitLeChameau: Et, étrangement, on ne parle presque pas de ça... Pas sexy l'évasion fiscale? Regarde mon beau niqab?  https://t.co/yW…\",\n",
       " 'Read this!  How Stephen Harper changed the character of Canada: Goar http://t.co/eupNyUUzxz via @torontostar',\n",
       " '@EmileeAnschutz @KTalbert22 Harper will have to pay rent...in cuteness and smiles!',\n",
       " 'Selling Canada out to corporate interests? https://t.co/Ca6EImC58y',\n",
       " \"RT @___Danno: @stephenlautens If anything should be investigated it's Harper seizing control of Imigration Canada for political purposes #c…\",\n",
       " 'RT @albertarabbit: @DuaneZaraska #Harper is interfering with Canada’s justice system. It never stops! #time4change ! #cdnpoli http://t.co/V…',\n",
       " '@OutlawTory @TNorrisYEG @BreezyXC60 Not when Harper was making shady deals behind the presidents back',\n",
       " 'MASTER COACH UPDATE | \\nEvery SUNDAY Master Coaches Janet Kane &amp; Craig Harper will be bringing you a… https://t.co/ijmbFiD5Gi',\n",
       " 'RT @jofo2005: Another nail in the coffin for Harper! #elexn42 http://t.co/wHBYBHXkWL',\n",
       " \"RT @nytimes: In Canada, Stephen Harper's office intervened to slow Syrian asylum claims\\nhttp://t.co/JQWcPAq3kF http://t.co/etXq1zRuWQ\",\n",
       " 'The Trans-Pacific Partnership puts democracy up for sale. Thanks for nothing Harper.http://t.co/Hy22fRJVsl … #TPP #cdnpoli #cpc #lpc',\n",
       " \"Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/2Z16O5fkFI #elxn42\",\n",
       " 'MASTER COACH UPDATE | \\nEvery SUNDAY Master Coaches Janet Kane &amp; Craig Harper will be bringing you a special 5... http://t.co/QlFogQfefs',\n",
       " 'RT @MATUGAMATUGA: Only one of the reasons the Cons cut important programs for Seniors and Vets? https://t.co/ABrfD9QF1J',\n",
       " 'RT @Sikhchic: Years Ago, Canada’s Prime Minister Stephen Harper Launched His Political Career By Trying … http://t.co/FDz8RA5n9P http://t.c…',\n",
       " \"RT @Raffi_RC: what Harper's divide &amp; inflame politics is doing across this country. #elxn42 #countrywewant  https://t.co/cQEz4dapij\",\n",
       " 'RT @Go4Darrell: @MinJoeOliver you and Harper have my vote!\\n\\nJust kidding.\\n\\n#RealChange\\n\\n#TeamTrudeau\\n\\n#cdnpoli',\n",
       " 'RT @SalluLicious: ★(HQ/Huge) EXTRAVAGANT..Scans of @BeingSalmanKhan @sonamakapoor from Harper’s Bazaar Bride http://t.co/vpy8xm5OCw http://…',\n",
       " \"#Bigots in power? #HarrySmith: #Harper's #Cultural War on #Muslim Women Must End | The Tyee http://t.co/mixx421k8f via @TheTyee\",\n",
       " \"I'M ABLE TO VOTE TOMORROW I THOUGHT I WASNT GONNA GET TO!!! FUCK IT UP!!! BYE HARPER!!!\",\n",
       " '【名入れ\\u3000ウィスキー】【名入れ彫刻ボトル/彫刻グラス】【選べる17色！イニシャル×オリジナルラベル\\u3000デザインH案】【ウイスキー】I.W.HARPER 700ml （名入れ/ウィスキー/イニシャル/オリ http://t.co/OWuWNRnwqJ',\n",
       " 'Good boy. https://t.co/x1tNXlbC5f',\n",
       " \"@globalnews @CO2_unFiltered If Mulcair were smart, he'd offer to join a Harper government to defeat the Liberals. http://t.co/FE9xx70zrQ\",\n",
       " 'Hoping for a strong majority but as long as Harper is gone I will settle for another result! https://t.co/HdgBkjxak3',\n",
       " 'RT @HuffPostQuebec: Harper vise les poches des Canadiens #polcan #fed2015 http://t.co/vvwJLuMGql http://t.co/ynxHUOSYTH',\n",
       " \"Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/nwat74d9qv #elxn42\",\n",
       " 'RT @dawatchdawg: @MPJulian Voting for the NDP means 4 more years of #Harper.  Maybe next time Mr.. Mulcair, this election is too important,…',\n",
       " \"RT @MrDash109: In 2008 election Harper said  Liberal Party will run deficits! Then Harper ran 7 in a row. He's clearly out of his league. #…\",\n",
       " 'RT @mes200000: Vote https://t.co/4YluBO7GM5',\n",
       " '@Go4Darrell @2010redmittens Mr @MinJoeOliver Harper wrote to best Hockey book ever . I`m kidding too .',\n",
       " 'RT @ActGroh: Harper Hates You!! http://t.co/Y5m69ne60f via @HumansvsHarper\\n#HeaveSteve #elxn42 #cdnpoli',\n",
       " '#Harper \"book-burning\" #science #library closures since 2010 while lavishing $ on religion and oil #cdnpoli #elxn42 http://t.co/tdHsg1Grco',\n",
       " 'Why is the media giving Trudeau kid glove treatment, aka Obama, and we know how that worked out?  https://t.co/AameiIBAU2',\n",
       " '#Nats OF Bryce Harper has dyed his hair grey. New best hair in #MLB? (Photo credit: @Cut4) http://t.co/DZfICYgtP8',\n",
       " \"Our economy is in the worst shape it's been in years. Stop listening to Harper saying he knows what he's doing. He doesn't.\",\n",
       " '@Sue_Lib As if Harper gives a..bean!  Made his bones dissin Canada. American mentor hates our Charter of Rights &amp; Freedoms? #cdnpoli #Elxn42',\n",
       " 'Maybe Bryce Harper’s going as Ursula the sea witch for Halloween.',\n",
       " \"Don't be a fucking idiot. Check out this sweary, angry yet accurate report on Stephen Harper http://t.co/P3LrEBEVMt #elxn42\",\n",
       " \"Bien d'accord \\nDes Inuites se voilent pour attirer l’attention de Stephen Harper | JDQ http://t.co/sTZjeMEXEV\",\n",
       " 'RT @pressprogress: Harper wondered if disaster aid after Quebec flood was special treatment? http://t.co/jLmsba4mTy #elxn42 http://t.co/XLi…',\n",
       " 'Outdated fact or snarky statement about the second book, you decide! https://t.co/0wxmwF7wNN',\n",
       " \"friends don't let friends vote harper\",\n",
       " 'RT @theninjagreg: Chewy peed on a Stephen Harper campaign sign #elxn41 #TMLtalk',\n",
       " '@foryourhands yeah but is he using his online presence to GET HARPER OUT',\n",
       " \"RT @mustangmadd: sorry lose all respect for any1 let's NDP spew this utter nonsense n mislead lesson 1 u have no seat no1 does CLEAR? https…\",\n",
       " 'RT @cmusician: NDP will reverse Harper’s cuts to the Canada Health Transfer &amp; will ensure the transfer increases by at least 6%/yr. #elxn42…',\n",
       " \"RT @PObean: RT So happy you voted! This early turnout bodes well for Canada! Can't wait to see the back of &amp; bring back our de… https://t.c…\",\n",
       " 'RT @Davejonesy: Strategic voters, especially in #yegcentre, read this - @randyb4yeg &amp; #LPC are the team to oust Harper.  https://t.co/PRCj4…',\n",
       " 'RT @TheTyee: Strategic Deal in 16 Key Ridings Can Scuttle Harper: Tech Pro http://t.co/6OWdUImq3c #elxn42 http://t.co/FlIphVCtW7',\n",
       " \"RT @hydroqueen: Harper brand collapses - desperate #cpc go to ads that say it's not about Harper. When you get rid of him as leader - let u…\",\n",
       " '#Radionomy #TuneIn #Nowplaying #Ben Harper #Faithfully Remain http://t.co/9uICs3F95g',\n",
       " 'RT This_is_D_Klatt \"#Nats OF Bryce Harper has dyed his hair grey. New best hair in #MLB? (Photo credit: Cut4) http://t.co/CjDj3hhC94\"',\n",
       " \"I don't understand why Obama being petty &amp; vindictive is a reason not to vote for Harper. #KeystoneXL #Elxn42 http://t.co/Lk3jHUn3p6\",\n",
       " \"RT @___Danno: @stephenlautens If anything should be investigated it's Harper seizing control of Imigration Canada for political purposes #c…\",\n",
       " 'RT @jgirvin: Canada Boot Harper @pmharper #cpc @jkenney @PierrePoilievre @RonaAmbrose #heavesteve http://t.co/QdWGTSw2Vn',\n",
       " 'RT @ABCVeterans2015: Dr.W Winegard fought in WWII\\nHe is calling on Canadians to DEFEAT HARPER on Oct 19 \\n#cdnpoli #onpoli #bcpoli #elxn42 h…',\n",
       " \"8 dirty words the Harper Government doesn't want you to know.\\n\\n#stopharper #cdnpoli http://t.co/n5JiG8Tfq8\",\n",
       " 'RT @ABCVeterans2015: If you stand with #veterans, please vow to vote against #Harper Oct 19! #cdnpoli #elxn42 #canpoli #onpoli #bcpoli http…',\n",
       " 'RT @RCIisLeaking: RCMP grab protester during a campaign event by Conservative Liar Stephen Harper in Surrey, B.C. Thursday. #cdnpoli http:/…',\n",
       " 'RT @cbagin: Harper clear choice on the economy | EDITORIAL http://t.co/dr3axKkomE',\n",
       " '... says any Canadian paying attention (I hope) https://t.co/5oSSZOOD4a',\n",
       " 'Harper Interfering With Justice System With Election Ad: Lawyers http://t.co/UE4ciV194d',\n",
       " 'RT @almondfact: stephen harper and umi sonoda matching UR set http://t.co/YHvsGBwyL4',\n",
       " 'RT @PaulHBeckwith: #Harper penny-pinched on #science libraries while lavishing funds on religion and oil http://t.co/9x3zo4BnRL #NDP #LPC #…',\n",
       " 'MT @Sikhchic: Yrs Ago, Canada’s PM Stephen Harper Launched His Political Career By Trying … http://t.co/BEIwN1Nwlj #Surrey #bcpoli #elxn42',\n",
       " 'RT @Sue_Lib: Harper’s election ad about mentally ill father interferes with justice system: lawyers http://t.co/k2EWsjp5Ml  #cdnpoli #elxn42',\n",
       " 'Go #vote, young ones!\\n\\nHarper cut millions of art grants, minimized education funding, cut most of the funding... http://t.co/9RVgRTsQyT',\n",
       " 'RT @BBurris1322: Mavs have had 11 head coaches since 1968. Only 3 have beaten Longview. Dennis Parker, Bill Harper &amp; Clint Harper. http://t…',\n",
       " 'RT @Proof84801544: @1planet_People your an idiot. Harper best prime minister in last 40 yrs.  your a regressive liberal and make no sense',\n",
       " 'RT @JustinTrudeau: To stop Stephen Harper, we need you to vote. Find your advance polling location: http://t.co/RtSzoTP9cc http://t.co/GOfO…',\n",
       " 'RT @BaseballBros: Bryce Harper is looking a little icy http://t.co/SStGN4qpMu',\n",
       " \"RT @ParlHowl: What's that about only needing 35 seats @NDP_HQ? How many will Harper need for another majority, then? http://t.co/x7RTowwbeZ\",\n",
       " 'Canada: The Cover-Up and Steal of Another Election. The Harper Corruption of Canada Opposition Fear  https://t.co/OHOiiF7xVL via @grtvnews',\n",
       " 'Canada: The Cover-Up and Steal of Another Election. The Harper Corruption of Canada Opposition Fear  http://t.co/NhAI8o5DhO via @grtvnews',\n",
       " 'MNWA would like to extend a heartfelt congratulations to @charley4805 today on the birth of his daughter, Harper Harley. Awesome name.']"
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