silhouette_plot_sig_strings.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#import relevant packages\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.metrics import silhouette_samples,silhouette_score\n",
    "import matplotlib.cm as cm\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#read in clustered data\n",
    "data = pd.read_csv(\"fcc_comments_clustered.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#calculate silhouette scores\n",
    "features = data.iloc[:,-384:]\n",
    "labels = data[\"cluster_id\"]\n",
    "silhouette_score = silhouette_score(features,labels)\n",
    "silhouette_samp_scores = silhouette_samples(features,labels)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ASZIkSZK0esybqIiI04DHANeSu35cXdr8beB64C+B7wIfLtbvXdowpYXZtm0b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\nANAYggoAAACgMQQVAAAAQGMIKgAAAIDGEFQAAAA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rwx5R8dYkN9ZaL03y7Ul+rJRyR2/d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\nIiIiIiK58f8Bq2Sf7M5hx6AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f42d344b8d0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#used code from here to make silhouette plots:\n",
    "# http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html\n",
    "fig,ax1 = plt.subplots(1, 1)\n",
    "fig.set_size_inches(18, 18)\n",
    "\n",
    "ax1.set_xlim([-0.2, 1])\n",
    "# The (n_clusters+1)*10 is for inserting blank space between silhouette\n",
    "# plots of individual clusters, to demarcate them clearly.\n",
    "n_clusters = 50\n",
    "#ax1.set_ylim([0, len(features) + (n_clusters + 1) * 10]);\n",
    "\n",
    "y_lower = 10\n",
    "for i in range(n_clusters):\n",
    "    # Aggregate the silhouette scores for samples belonging to\n",
    "    # cluster i, and sort them\n",
    "    ith_cluster_silhouette_values = \\\n",
    "        silhouette_samp_scores[labels == i]\n",
    "\n",
    "    ith_cluster_silhouette_values.sort()\n",
    "\n",
    "    size_cluster_i = ith_cluster_silhouette_values.shape[0]\n",
    "    y_upper = y_lower + size_cluster_i\n",
    "\n",
    "    color = cm.spectral(float(i) / n_clusters)\n",
    "    ax1.fill_betweenx(np.arange(y_lower, y_upper),\n",
    "                      0, ith_cluster_silhouette_values,\n",
    "                      facecolor=color, edgecolor=color, alpha=0.7)\n",
    "\n",
    "    # Label the silhouette plots with their cluster numbers at the middle\n",
    "    ax1.text(-0.25, y_lower + 0.5 * size_cluster_i, str(i),fontsize=12)\n",
    "    \n",
    "    # A dab at the average silhouette score for cluster i (Kao)\n",
    "    ax1.scatter(x=ith_cluster_silhouette_values.mean(), y=y_lower + 0.5 * size_cluster_i, color='k');\n",
    "\n",
    "    # Compute the new y_lower for next plot\n",
    "    y_lower = y_upper + 10  # 10 for the 0 samples\n",
    "    \n",
    "    \n",
    "ax1.set_title(\"Silhouette Plot for Vectorized Comments\",fontsize=26)\n",
    "ax1.set_xlabel(\"Silhouette coefficient values\",fontsize=18)\n",
    "\n",
    "ax1.set_yticks([])  # Clear the yaxis labels / ticks\n",
    "ax1.set_xticks([-0.2,0, 0.2, 0.4, 0.6, 0.8, 1])\n",
    "ax1.set_xticklabels([-0.2,0, 0.2, 0.4, 0.6, 0.8, 1],fontsize=18);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#find signature strings for each cluster\n",
    "sig_strings = pd.DataFrame()\n",
    "sig_strings[\"cluster_id\"] = np.arange(0,labels.max()+1)\n",
    "comm_list = list()\n",
    "sil_mean = list()\n",
    "\n",
    "for ii in range(labels.max()+1):\n",
    "    text = data[data[\"cluster_id\"] == ii].reset_index(drop=True)\n",
    "    ind = np.random.randint(0,len(text))\n",
    "    comm_list.append(text[\"text_data\"][ind])\n",
    "    ith_cluster_silhouette_values = silhouette_samp_scores[labels == ii]\n",
    "    sil_mean.append(ith_cluster_silhouette_values.mean())\n",
    "\n",
    "sig_strings[\"mean silhouette score\"] = sil_mean\n",
    "sig_strings[\"text_data\"] = comm_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "cluster_mean_sil = dict()\n",
    "for ii in range(len(sig_strings)):\n",
    "    cluster_mean_sil[sig_strings[\"cluster_id\"][ii]] = sig_strings[\"mean silhouette score\"][ii]\n",
    "    \n",
    "cluster_means = list()\n",
    "for jj in range(len(data)):\n",
    "    cluster_means.append(cluster_mean_sil[data[\"cluster_id\"][jj]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "data2 = pd.DataFrame()\n",
    "data2[\"mean silhouette score\"] = cluster_means\n",
    "data2[\"silhouette_score\"] = silhouette_samp_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "views = [1,1,1,1,1,1,1,1,1,1,\n",
    "        1,1,1,1,1,1,1,1,1,1,\n",
    "        1,1,1,1,1,1,1,1,2,1,\n",
    "        1,0,1,1,1,0,1,1,1,1,\n",
    "         1,1,1,1,1,1,1,1,1,1]\n",
    "\n",
    "cluster_views = dict()\n",
    "for ii in range(len(sig_strings)):\n",
    "    cluster_views[sig_strings[\"cluster_id\"][ii]] = views[ii]\n",
    "    \n",
    "nn_stance = list()\n",
    "for jj in range(len(data)):\n",
    "    nn_stance.append(cluster_views[data[\"cluster_id\"][jj]])\n",
    "    \n",
    "data2[\"net neutrality\"] = nn_stance\n",
    "data2 = pd.concat([data[\"cluster_id\"],data2[\"silhouette_score\"],data2[\"mean silhouette score\"],\n",
    "                   data2[\"net neutrality\"],data[\"confirmation_number\"],data[\"text_data\"]],axis=1)\n",
    "data2.to_csv(\"fcc_comments_cluster_silmean.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#calculate number of comments per cluster\n",
    "comm_counts = list()\n",
    "for jj in range(50):\n",
    "    val = 0\n",
    "    for ii in range(len(data[\"cluster_id\"])):\n",
    "        if data[\"cluster_id\"][ii] == jj:\n",
    "            val = val + 1\n",
    "    comm_counts.append(val)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "colors = list()\n",
    "for view in views:\n",
    "    if view == 1:\n",
    "        colors.append('g')\n",
    "    elif view == 0:\n",
    "        colors.append('r')\n",
    "    else:\n",
    "        colors.append('b')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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M/HVQROzRyDYezF8PjojvlhKiiKiJiB+S/dB4qy12plxKaSb5oDnAFRExvvTjOSI6RcR2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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f42dcec6128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig2 = plt.figure(figsize=(15,10))\n",
    "\n",
    "plt.bar(np.arange(0,50),comm_counts,width=1,color=colors)\n",
    "plt.xticks(np.arange(0,50,1))\n",
    "plt.xlabel(\"Cluster ID\")\n",
    "plt.ylabel(\"# of comments\")\n",
    "#Kao\n",
    "patch1 = mpatches.Patch(color='g', label='Pro-net neutrality')\n",
    "patch2 = mpatches.Patch(color='r', label='Anti-net neutrality')\n",
    "plt.legend(handles=[patch1,patch2],fontsize=14)\n",
    "plt.title(\"Stance on net neutrality by cluster\",fontsize=24);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
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