lda_tuning.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c1ebde0b-23d7-4890-b34f-7096de1f4984",
   "metadata": {},
   "source": [
    "# Latent Dirichlet Allocation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "160d0508-e6b2-4c32-bd2e-cfd4bab9d8db",
   "metadata": {},
   "source": [
    "LDA is probably the most commonly evoked algorithm when talking about unsupervised topic modeling. Here, we look at what topics we can generate and use the coherence evaluation metric to give us an idea of how many topics to generate, as well as the alpha and eta parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "87f1c328-8050-48d5-9400-bac789906b99",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re \n",
    "import random\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "from gensim.models import LdaMulticore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "08839e66-2661-4a14-a36a-abfdbe3258bd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to /home/noe/nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    }
   ],
   "source": [
    "from helpers.preprocessing import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "45cdab85-a5d9-42d4-bb52-e908dcb4eb9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f7974c4d-9e24-4e19-aa9b-112ab4f9ab14",
   "metadata": {},
   "outputs": [],
   "source": [
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e5d9c2c-bf71-43ab-bb9f-dac4768599c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = load('data/impresso3.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8127697a-f460-44b4-b9f1-40dc0a2e6dd1",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>uid</th>\n",
       "      <th>type</th>\n",
       "      <th>language</th>\n",
       "      <th>title</th>\n",
       "      <th>size</th>\n",
       "      <th>country</th>\n",
       "      <th>newspaper</th>\n",
       "      <th>issue</th>\n",
       "      <th>pages</th>\n",
       "      <th>nb_pages</th>\n",
       "      <th>...</th>\n",
       "      <th>year</th>\n",
       "      <th>is_on_front</th>\n",
       "      <th>date</th>\n",
       "      <th>persons_mentioned</th>\n",
       "      <th>locations_mentioned</th>\n",
       "      <th>content</th>\n",
       "      <th>access_right</th>\n",
       "      <th>content_provider</th>\n",
       "      <th>is_content_available</th>\n",
       "      <th>[total:7120,available:7200]</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>JDG-1964-04-29-a-i0007</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>Un jour en Suisse\" sera insuffisant pour décou...</td>\n",
       "      <td>1185</td>\n",
       "      <td>CH</td>\n",
       "      <td>JDG</td>\n",
       "      <td>JDG-1964-04-29-a</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1964</td>\n",
       "      <td>False</td>\n",
       "      <td>1964-04-29 00:00:00+00:00</td>\n",
       "      <td>Les Sécuritas|M. Gabriel Despland, président|M...</td>\n",
       "      <td>Suisse|Lausanne|Suisse|Lausanne|Suisse|Lausanne</td>\n",
       "      <td>Un jour en Suisse \" sera insuffisant pour déco...</td>\n",
       "      <td>OpenPrivate</td>\n",
       "      <td>SNL</td>\n",
       "      <td>y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>GDL-1964-10-16-a-i0035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>Après une campagne de protestation 500 000 vis...</td>\n",
       "      <td>601</td>\n",
       "      <td>CH</td>\n",
       "      <td>GDL</td>\n",
       "      <td>GDL-1964-10-16-a</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1964</td>\n",
       "      <td>False</td>\n",
       "      <td>1964-10-16 00:00:00+00:00</td>\n",
       "      <td>M. Charles Apothéloz, directeur|M. Hans Giger|...</td>\n",
       "      <td>Suisse|Suisse|Lausanne|Lausanne|Bern|Suisse</td>\n",
       "      <td>Après une campagne de protestation 500 000 vis...</td>\n",
       "      <td>OpenPrivate</td>\n",
       "      <td>SNL</td>\n",
       "      <td>y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>luxland-1968-04-26-a-i0033</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>L'ordinateur n'est un épouvantail que pour les...</td>\n",
       "      <td>430</td>\n",
       "      <td>LU</td>\n",
       "      <td>luxland</td>\n",
       "      <td>luxland-1968-04-26-a</td>\n",
       "      <td>6</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1968</td>\n",
       "      <td>False</td>\n",
       "      <td>1968-04-26 00:00:00+00:00</td>\n",
       "      <td>Irving Adler, spécialiste américain</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Closed</td>\n",
       "      <td>BNL</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>EXP-1970-04-20-a-i0053</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>Â Bâle, la formation professionnelle horlogère</td>\n",
       "      <td>342</td>\n",
       "      <td>CH</td>\n",
       "      <td>EXP</td>\n",
       "      <td>EXP-1970-04-20-a</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1970</td>\n",
       "      <td>False</td>\n",
       "      <td>1970-04-20 00:00:00+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bâle|Bâle</td>\n",
       "      <td>Â Bâle, la formation professionnelle horlogère...</td>\n",
       "      <td>OpenPrivate</td>\n",
       "      <td>SNL</td>\n",
       "      <td>y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>IMP-1970-04-21-a-i0174</td>\n",
       "      <td>NaN</td>\n",
       "      <td>fr</td>\n",
       "      <td>NaN</td>\n",
       "      <td>324</td>\n",
       "      <td>CH</td>\n",
       "      <td>IMP</td>\n",
       "      <td>IMP-1970-04-21-a</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>...</td>\n",
       "      <td>1970</td>\n",
       "      <td>False</td>\n",
       "      <td>1970-04-21 00:00:00+00:00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Bâle</td>\n",
       "      <td>Stand «Formation professionnelle horlogère » à...</td>\n",
       "      <td>OpenPrivate</td>\n",
       "      <td>SNL</td>\n",
       "      <td>y</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          uid  type language  \\\n",
       "0      JDG-1964-04-29-a-i0007   NaN       fr   \n",
       "1      GDL-1964-10-16-a-i0035   NaN       fr   \n",
       "2  luxland-1968-04-26-a-i0033   NaN       fr   \n",
       "3      EXP-1970-04-20-a-i0053   NaN       fr   \n",
       "4      IMP-1970-04-21-a-i0174   NaN       fr   \n",
       "\n",
       "                                               title  size country newspaper  \\\n",
       "0  Un jour en Suisse\" sera insuffisant pour décou...  1185      CH       JDG   \n",
       "1  Après une campagne de protestation 500 000 vis...   601      CH       GDL   \n",
       "2  L'ordinateur n'est un épouvantail que pour les...   430      LU   luxland   \n",
       "3     Â Bâle, la formation professionnelle horlogère   342      CH       EXP   \n",
       "4                                                NaN   324      CH       IMP   \n",
       "\n",
       "                  issue pages  nb_pages  ...  year  is_on_front  \\\n",
       "0      JDG-1964-04-29-a     2         1  ...  1964        False   \n",
       "1      GDL-1964-10-16-a     3         1  ...  1964        False   \n",
       "2  luxland-1968-04-26-a     6         1  ...  1968        False   \n",
       "3      EXP-1970-04-20-a     3         1  ...  1970        False   \n",
       "4      IMP-1970-04-21-a    14         1  ...  1970        False   \n",
       "\n",
       "                       date  \\\n",
       "0 1964-04-29 00:00:00+00:00   \n",
       "1 1964-10-16 00:00:00+00:00   \n",
       "2 1968-04-26 00:00:00+00:00   \n",
       "3 1970-04-20 00:00:00+00:00   \n",
       "4 1970-04-21 00:00:00+00:00   \n",
       "\n",
       "                                   persons_mentioned  \\\n",
       "0  Les Sécuritas|M. Gabriel Despland, président|M...   \n",
       "1  M. Charles Apothéloz, directeur|M. Hans Giger|...   \n",
       "2                Irving Adler, spécialiste américain   \n",
       "3                                                NaN   \n",
       "4                                                NaN   \n",
       "\n",
       "                               locations_mentioned  \\\n",
       "0  Suisse|Lausanne|Suisse|Lausanne|Suisse|Lausanne   \n",
       "1      Suisse|Suisse|Lausanne|Lausanne|Bern|Suisse   \n",
       "2                                              NaN   \n",
       "3                                        Bâle|Bâle   \n",
       "4                                             Bâle   \n",
       "\n",
       "                                             content access_right  \\\n",
       "0  Un jour en Suisse \" sera insuffisant pour déco...  OpenPrivate   \n",
       "1  Après une campagne de protestation 500 000 vis...  OpenPrivate   \n",
       "2                                                NaN       Closed   \n",
       "3  Â Bâle, la formation professionnelle horlogère...  OpenPrivate   \n",
       "4  Stand «Formation professionnelle horlogère » à...  OpenPrivate   \n",
       "\n",
       "  content_provider is_content_available [total:7120,available:7200]  \n",
       "0              SNL                    y                         NaN  \n",
       "1              SNL                    y                         NaN  \n",
       "2              BNL                  NaN                         NaN  \n",
       "3              SNL                    y                         NaN  \n",
       "4              SNL                    y                         NaN  \n",
       "\n",
       "[5 rows x 21 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "654d1bde-a490-4076-853c-169bd46ffa4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    Un jour en Suisse \" sera insuffisant pour déco...\n",
       "1    Après une campagne de protestation 500 000 vis...\n",
       "2                                                  NaN\n",
       "3    Â Bâle, la formation professionnelle horlogère...\n",
       "4    Stand «Formation professionnelle horlogère » à...\n",
       "Name: content, dtype: object"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The column that we are interested in\n",
    "df.content.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e2970197-6fb4-46cf-a773-b0e9a39f69bc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(7120, 21)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "1101f7f7-c928-416c-a03a-047885dba934",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/media/Common/miniconda3/lib/python3.9/site-packages/pandas/core/generic.py:5516: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self[name] = value\n"
     ]
    }
   ],
   "source": [
    "# As our dataset was manually extracted using keywords, we did our best to manually remove irrelevant articles,\n",
    "# especially large ones\n",
    "# The cleanup function removes these as well as nan values and very short articles that are mostly advertisements\n",
    "df = cleanup(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4caf9721-5acd-4b60-ae35-f1d0e502da0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4352, 21)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# As we can see, we are left with a much smaller dataset\n",
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c39d5c0-95b5-455f-a0ac-425482f7eab8",
   "metadata": {},
   "source": [
    "### Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "313f8fc1-dcab-4223-9d12-e56d5cae3bf9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# spacy_prep removes stopwords, punctuation, numbers, and adds bigrams and entities\n",
    "data = spacy_prep(df.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "193a3304-9adc-4e17-9033-fd4da9f1ea7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Remove words that appear in more than 30% of the articles and words that appear less than 3 times\n",
    "min_words = 3\n",
    "max_freq = 0.3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6564cf51-7b6a-4bea-bead-c324b755b95d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# create_corpus creates a spacy dictionary and corpus \n",
    "dictionary, corpus = create_corpus(data, min_words, max_freq)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a4a4846-d5b8-411f-86e4-f1b828629d61",
   "metadata": {},
   "source": [
    "### LDA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a67f59cf-d05b-4844-a3c1-0b15cce21893",
   "metadata": {},
   "outputs": [],
   "source": [
    "from helpers.models import *"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cdc41cd5-5b2a-4b4d-98cd-1c17efd503b7",
   "metadata": {},
   "source": [
    "First, we can choose an arbitrary number of topics (5) and look at what kinds of topics are generated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "b6076d6a-b0e5-4b48-b1de-fd982048396f",
   "metadata": {},
   "outputs": [],
   "source": [
    "workers = 6\n",
    "passes = 10\n",
    "random_state = 123\n",
    "num_topics = 5\n",
    "lda_model = lda(dictionary, corpus, num_topics, workers, passes, random_state, None, None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "5e0c92d3-d55d-4b77-a7e9-6b52a8dbdeb3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0,\n",
       "  [('film', 0.0069710407),\n",
       "   ('enfant', 0.00598608),\n",
       "   ('jeune', 0.004223193),\n",
       "   ('voir', 0.0028155367),\n",
       "   ('histoire', 0.0024370425),\n",
       "   ('prendre', 0.0024238096),\n",
       "   ('vie', 0.0023739657),\n",
       "   ('annee', 0.0022975206),\n",
       "   ('image', 0.002252371),\n",
       "   ('fois', 0.0022471268)]),\n",
       " (1,\n",
       "  [('jeune', 0.004820364),\n",
       "   ('marche', 0.0038021025),\n",
       "   ('enfant', 0.0037621406),\n",
       "   ('annee', 0.0035461304),\n",
       "   ('million', 0.0034903085),\n",
       "   ('suisse', 0.0033885813),\n",
       "   ('ete', 0.0030146057),\n",
       "   ('franc', 0.0029001075),\n",
       "   ('pouvoir', 0.0025041115),\n",
       "   ('societe', 0.0023417978)]),\n",
       " (2,\n",
       "  [('pouvoir', 0.002882625),\n",
       "   ('offrir', 0.0027393934),\n",
       "   ('pokemon', 0.0026189792),\n",
       "   ('neuchatel', 0.0023844587),\n",
       "   ('ete', 0.002204082),\n",
       "   ('semaine', 0.0020882366),\n",
       "   ('prendre', 0.0019473681),\n",
       "   ('carte', 0.0019343833),\n",
       "   ('jouer', 0.0019324634),\n",
       "   ('ville', 0.0019107787)]),\n",
       " (3,\n",
       "  [('console', 0.008508541),\n",
       "   ('nintendo', 0.007158203),\n",
       "   ('playstation', 0.0053077997),\n",
       "   ('titre', 0.004126778),\n",
       "   ('mode', 0.0039006781),\n",
       "   ('ecran', 0.0035880217),\n",
       "   ('mario', 0.0034061153),\n",
       "   ('course', 0.0032287769),\n",
       "   ('version', 0.00310889),\n",
       "   ('personnage', 0.0030457454)]),\n",
       " (4,\n",
       "  [('film', 0.004469135),\n",
       "   ('suisse', 0.0043789037),\n",
       "   ('jeune', 0.0035874473),\n",
       "   ('jour', 0.003213508),\n",
       "   ('ete', 0.0025770962),\n",
       "   ('ordinateur', 0.0024710733),\n",
       "   ('stereo', 0.0021111865),\n",
       "   ('public', 0.0020025475),\n",
       "   ('pouvoir', 0.0019516447),\n",
       "   ('semaine', 0.0019281224)])]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lda_model.show_topics(formatted=False, num_topics=5, num_words = 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "0f5d8c95-ef7c-447d-91d1-77bdf18cfe46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Here we can see that the importance of words in each topic decreases pretty significantly\n",
    "plt.rcParams['figure.figsize'] = 8, 6 \n",
    "plt.rcParams['font.size'] = 12\n",
    "\n",
    "# top 100 words by weight in each topic\n",
    "top_words = 100\n",
    "topics = lda_model.show_topics(\n",
    "    num_topics = 20, num_words = top_words, formatted = False)\n",
    "\n",
    "for _, infos in topics:\n",
    "    probs = [prob for _, prob in infos]\n",
    "    plt.plot(range(top_words), probs)\n",
    "\n",
    "plt.xlabel('Word rank')\n",
    "plt.ylabel('Probability')\n",
    "plt.title('Probabilities of Top 100 Words in each Topic')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fe52e339-ddf0-4c52-9076-ff0113832940",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# total weight assigned by each topic to its top 10 words\n",
    "top_probs = []\n",
    "top_n_words = 10\n",
    "topics = lda_model.show_topics(num_words = top_n_words, formatted = False, num_topics=5)\n",
    "for _, infos in topics:\n",
    "    prob = sum([prob for _, prob in infos])\n",
    "    top_probs.append(prob)\n",
    "\n",
    "ind = np.arange(5)\n",
    "width = 0.5\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "ax.bar(ind - (width / 2), top_probs, width, color = 'lightcoral')\n",
    "ax.set_xticks(ind)\n",
    "\n",
    "plt.xlabel('Topic')\n",
    "plt.ylabel('Probability')\n",
    "plt.title('Total Probability of Top 10 Words in each Topic')\n",
    "plt.xlim(-0.5, 4.5)\n",
    "plt.ylim(0, 0.15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "97c2a190-0a44-49b3-b537-287e3ca21783",
   "metadata": {},
   "source": [
    "We can see that top 10 words for a topic don't even account for 5% of the topic's total probability mass."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdd1319b-abf9-433d-bb15-101170462e4c",
   "metadata": {},
   "source": [
    "### Hyperparameter Tuning"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d616556-3590-4248-9ce0-0659b110919f",
   "metadata": {},
   "source": [
    "Now let's look at which number of topics gives the best coherence.\n",
    "\n",
    "alpha is a parameter that controls the prior distribution over topic weights in each document, while eta is a parameter for the prior distribution over word weights in each topic.\n",
    "\n",
    "A higher alpha makes the document preferences \"smoother\" over topics, and a higher eta makes the topic preferences \"smoother\" over words.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fbb32d74-caeb-424f-80d6-14ab89a724cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Look at coherences with the default alpha and eta\n",
    "workers = 6\n",
    "passes = 5\n",
    "random_state =123\n",
    "n_topics = np.arange(6, 18)\n",
    "coherences_1 = []\n",
    "coherences_2 = []\n",
    "models = []\n",
    "for n in n_topics:\n",
    "    lda_model = lda(dictionary, corpus, n, workers, passes, random_state, None, None)\n",
    "    models.append(lda_model)\n",
    "    coherences_1.append(compute_coherence(lda_model, data, corpus, dictionary, 'c_v'))\n",
    "    coherences_2.append(compute_coherence(lda_model, data, corpus, dictionary, 'u_mass'))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "66da951d-1a52-4883-96e7-ec51ebfdfea1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_topics</th>\n",
       "      <th>c_v</th>\n",
       "      <th>u_mass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.397807</td>\n",
       "      <td>-1.461332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.374710</td>\n",
       "      <td>-1.487827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.366287</td>\n",
       "      <td>-1.474992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.363595</td>\n",
       "      <td>-1.546207</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.353844</td>\n",
       "      <td>-1.584117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.352181</td>\n",
       "      <td>-1.635198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>14.0</td>\n",
       "      <td>0.351721</td>\n",
       "      <td>-1.640127</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num_topics       c_v    u_mass\n",
       "1         7.0  0.397807 -1.461332\n",
       "2         8.0  0.374710 -1.487827\n",
       "0         6.0  0.366287 -1.474992\n",
       "3         9.0  0.363595 -1.546207\n",
       "5        11.0  0.353844 -1.584117\n",
       "7        13.0  0.352181 -1.635198\n",
       "8        14.0  0.351721 -1.640127"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_topics = np.arange(6, 18)\n",
    "coherence_df1 = pd.DataFrame([n_topics, coherences_1, coherences_2]).transpose()\n",
    "coherence_df1.columns = ['num_topics', 'c_v', 'u_mass']\n",
    "coherence_df1 = coherence_df1.sort_values(by = 'c_v', ascending=False)\n",
    "coherence_df1.head(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "2faf45a0-e887-440c-a4b6-a76c37454974",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here are the results without running above cells\n",
    "coherence_df1 = pd.read_csv(\"coherence/default_ae_coherence.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e1907da3-4fac-4dd6-8bee-84a8ec89f694",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Don't run --- takes a long time\n",
    "# Try topic sizes from 6 to 16 and compute coherences (for the entire corpus)\n",
    "# Try alpha and eta values\n",
    "\n",
    "workers = 6\n",
    "passes = 5\n",
    "random_state =123\n",
    "n_topics = np.arange(6, 17)\n",
    "alphas = [20, 0.01, 0.05]\n",
    "etas = [20, 0.01, 0.05]\n",
    "coherences_1 = []\n",
    "coherences_2 = []\n",
    "models = []\n",
    "passed = []\n",
    "alphas_col = []\n",
    "etas_col = []\n",
    "for n in n_topics:\n",
    "    for a in alphas:\n",
    "        for e in etas:\n",
    "            # some values give an underflow error\n",
    "            try:\n",
    "                lda_model = lda(dictionary, corpus, n, workers, passes, random_state, a, e)\n",
    "                models.append(lda_model)\n",
    "                coherences_1.append(compute_coherence(lda_model, data, corpus, dictionary, 'c_v'))\n",
    "                coherences_2.append(compute_coherence(lda_model, data, corpus, dictionary, 'u_mass'))\n",
    "                alphas_col.append(a)\n",
    "                etas_col.append(e)\n",
    "            except:\n",
    "                passed.append((n, a, e))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "a65197ac-ce67-44b4-b4f4-54e795646e84",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_topics</th>\n",
       "      <th>alpha</th>\n",
       "      <th>eta</th>\n",
       "      <th>c_v</th>\n",
       "      <th>u_mass</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>7.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.390164</td>\n",
       "      <td>-1.456707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>8.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.368559</td>\n",
       "      <td>-1.486627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.368368</td>\n",
       "      <td>-1.474733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>9.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.365530</td>\n",
       "      <td>-1.527821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>11.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.355659</td>\n",
       "      <td>-1.584626</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>14.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.353315</td>\n",
       "      <td>-1.652299</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>13.0</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.05</td>\n",
       "      <td>0.351852</td>\n",
       "      <td>-1.635522</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    num_topics  alpha   eta       c_v    u_mass\n",
       "9          7.0   0.05  0.05  0.390164 -1.456707\n",
       "14         8.0   0.05  0.05  0.368559 -1.486627\n",
       "4          6.0   0.05  0.05  0.368368 -1.474733\n",
       "19         9.0   0.05  0.05  0.365530 -1.527821\n",
       "29        11.0   0.05  0.05  0.355659 -1.584626\n",
       "44        14.0   0.05  0.05  0.353315 -1.652299\n",
       "39        13.0   0.05  0.05  0.351852 -1.635522"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Don't run -- can read in results in cell below\n",
    "# Create a dataframe looking at the coherence values for the different number of topics and alphas and etas\n",
    "n_topics = np.repeat(np.arange(6, 17), 5)\n",
    "coherence_df = pd.DataFrame([n_topics, alphas_col, etas_col, coherences_1, coherences_2]).transpose()\n",
    "coherence_df.columns = ['num_topics', 'alpha', 'eta', 'c_v', 'u_mass']\n",
    "coherence_df = coherence_df.sort_values(by = 'c_v', ascending=False)\n",
    "coherence_df.head(7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "76b7a546-8880-436b-a757-67429a7811c2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Results without running above cells\n",
    "coherence_df = pd.read_csv(\"coherence/tuning2.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d53974c-cdfc-418e-9db9-072e3a4b4bcd",
   "metadata": {},
   "source": [
    "We can see that the best c_v and u_mass coherence is achieved for 7 topics with alpha 0.05 and eta 0.05. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "8c83b35c-7f9a-44d7-a069-cdb862ccf778",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x14039b790>"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the coherence for the different combinations\n",
    "coherencedf_20_20 = coherence_df[(coherence_df.alpha == 20) & (coherence_df.eta == 20)].sort_values(by = 'num_topics')\n",
    "coherencedf_20_01 = coherence_df[(coherence_df.alpha == 20) & (coherence_df.eta == 0.01)].sort_values(by = 'num_topics')\n",
    "coherencedf_20_05 = coherence_df[(coherence_df.alpha == 20) & (coherence_df.eta == 0.05)].sort_values(by = 'num_topics')\n",
    "coherencedf_05_20 = coherence_df[(coherence_df.alpha == 0.05) & (coherence_df.eta == 20)].sort_values(by = 'num_topics')\n",
    "coherencedf_05_05 = coherence_df[(coherence_df.alpha == 0.05) & (coherence_df.eta == 0.05)].sort_values(by = 'num_topics')\n",
    "\n",
    "plt.plot(coherencedf_20_20.num_topics, coherencedf_20_20.c_v, label = \"alpha = 20, eta = 20\")\n",
    "plt.plot(coherencedf_20_01.num_topics, coherencedf_20_01.c_v, label = \"alpha = 20, eta = 0.01\")\n",
    "plt.plot(coherencedf_20_05.num_topics, coherencedf_20_05.c_v, label = \"alpha = 20, eta = 0.05\")\n",
    "plt.plot(coherencedf_05_20.num_topics, coherencedf_05_20.c_v, label = \"alpha = 0.05, eta = 20\")\n",
    "plt.plot(coherencedf_05_05.num_topics, coherencedf_05_05.c_v, label = \"alpha = 0.05, eta = 0.05\")\n",
    "plt.title(\"Coherence by Number of Topics\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d12d263b-a93a-4530-a7aa-a6efa706c7d1",
   "metadata": {},
   "source": [
    "Another way that we can evaluate the models is by creating a training and testing set and then computing the perplexity on the test set."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce5b618f-1620-47fd-8b09-372ec58c9b3e",
   "metadata": {},
   "source": [
    "### Train and Test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "30796333-dde7-4f7c-a26d-76c9e6488d78",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/meghanharrington/ml-project-2-turboml/helpers/preprocessing.py:209: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
      "  content=np.array(data)\n"
     ]
    }
   ],
   "source": [
    "# Choose 80% of the articles for training and 20% for testing\n",
    "train, test = train_test_split(data, 0.8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "6de564fe-2294-4c84-9736-aedc94de9984",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a dictionary and a corpus for the train data and create a test corpus based on the training dictionary\n",
    "dictionary_train, corpus_train = create_corpus(train, min_words, max_freq)\n",
    "corpus_test = create_test_corpus(dictionary_train, test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e0d5272-e60c-4b75-bbc0-bb2cb0f2f64a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here we will just look at perplexity\n",
    "workers = 6\n",
    "passes = 5\n",
    "random_state =123\n",
    "num_words = 10\n",
    "# based on previous results we can look at a tighter range of topics\n",
    "n_topics = np.arange(8, 16)\n",
    "coherences_1 = []\n",
    "coherences_2 = []\n",
    "perplexities = []\n",
    "for n in n_topics:\n",
    "    lda_model = lda(dictionary_train, corpus_train, n, workers, passes, random_state, _, _)\n",
    "    perplexities.append(compute_perplexity(lda_model, corpus_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "1a71934a-00dc-443e-9b7a-6a1a49f4346b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_topics</th>\n",
       "      <th>perplexity</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>15.0</td>\n",
       "      <td>-10.557676</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>14.0</td>\n",
       "      <td>-10.539429</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>13.0</td>\n",
       "      <td>-10.518393</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12.0</td>\n",
       "      <td>-10.494238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11.0</td>\n",
       "      <td>-10.466161</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>10.0</td>\n",
       "      <td>-10.433085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>9.0</td>\n",
       "      <td>-10.394000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>8.0</td>\n",
       "      <td>-10.347472</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   num_topics  perplexity\n",
       "7        15.0  -10.557676\n",
       "6        14.0  -10.539429\n",
       "5        13.0  -10.518393\n",
       "4        12.0  -10.494238\n",
       "3        11.0  -10.466161\n",
       "2        10.0  -10.433085\n",
       "1         9.0  -10.394000\n",
       "0         8.0  -10.347472"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perplexity_df = pd.DataFrame([n_topics, perplexities]).transpose()\n",
    "perplexity_df.columns = ['num_topics', 'perplexity']\n",
    "perplexity_df.sort_values(by = 'perplexity')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e8c5dcf-2df5-4864-bdec-e1c7f9f81ad1",
   "metadata": {},
   "source": [
    "This doesn't appear to be a very helpful metric, the perplexities are monotone decreasing as topics increase."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "20a330a6-d380-4297-adc1-d9c8e5a88f34",
   "metadata": {},
   "source": [
    "# Generate topics"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0fcba7c0-fd0c-4e79-8c38-ed1d668585a5",
   "metadata": {},
   "source": [
    "Although the model with 7 topics had the highest coherence, with topic modeling the best evaluation is looking at the topics manually. It seems like with 9 topics, we get a bit more variety. So we can load the trained lda model with 9 topics and alpha and eta parameters of 0.05.\n",
    "\n",
    "**Important note:** the following analysis rely on the topics generated by our model at the time.\n",
    "The documentation of `lda_model.show_topics` seems to say that the returned topics might change on different run of the model; thus the following analysis might be off if you try to retrain the model again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "574f5566-32bd-44a8-b902-6516d77f1d3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load pretrained LDA Model to be used\n",
    "lda_model = LdaMulticore.load(\"models/model_9_05_05.lda\")\n",
    "\n",
    "# To train the model\n",
    "# lda_model = lda(dictionary, corpus, 9, workers, passes, random_state, 0.05, 0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "fe537f52-37b3-4612-99c1-31734126ec2a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0,\n",
       "  [('console', 0.009812394),\n",
       "   ('nintendo', 0.007766979),\n",
       "   ('playstation', 0.0046109883),\n",
       "   ('sony', 0.004050902),\n",
       "   ('machine', 0.003290493),\n",
       "   ('ecran', 0.0031547493),\n",
       "   ('super', 0.0029830923),\n",
       "   ('cartouche', 0.0027458032),\n",
       "   ('sega', 0.0026806663),\n",
       "   ('suisse', 0.002668474),\n",
       "   ('offrir', 0.0026008056),\n",
       "   ('mario', 0.0025557762),\n",
       "   ('prix', 0.0024679613),\n",
       "   ('annee', 0.0023843648),\n",
       "   ('enfant', 0.0023799601)]),\n",
       " (1,\n",
       "  [('pouvoir', 0.003800191),\n",
       "   ('film', 0.0037765354),\n",
       "   ('console', 0.0036592416),\n",
       "   ('combat', 0.0034860547),\n",
       "   ('propose', 0.0026860684),\n",
       "   ('ecran', 0.002633324),\n",
       "   ('coup', 0.002473909),\n",
       "   ('playstation', 0.0024595342),\n",
       "   ('action', 0.0024416964),\n",
       "   ('jour', 0.002367328),\n",
       "   ('nintendo', 0.0023626431),\n",
       "   ('mission', 0.002354833),\n",
       "   ('mario', 0.0023145827),\n",
       "   ('personnage', 0.0023083698),\n",
       "   ('ete', 0.0021666628)]),\n",
       " (2,\n",
       "  [('film', 0.006178176),\n",
       "   ('jeune', 0.0034489261),\n",
       "   ('suisse', 0.0030741226),\n",
       "   ('course', 0.0028587028),\n",
       "   ('mode', 0.0027798107),\n",
       "   ('histoire', 0.0025992002),\n",
       "   ('ecran', 0.0023346883),\n",
       "   ('voir', 0.00231352),\n",
       "   ('pouvoir', 0.002283372),\n",
       "   ('playstation', 0.002275937),\n",
       "   ('jour', 0.0022171424),\n",
       "   ('voiture', 0.0021730277),\n",
       "   ('fois', 0.0021343075),\n",
       "   ('stereo', 0.0020388085),\n",
       "   ('console', 0.0019708714)]),\n",
       " (3,\n",
       "  [('enfant', 0.0034001465),\n",
       "   ('film', 0.0033064946),\n",
       "   ('suisse', 0.0031191423),\n",
       "   ('heure', 0.0030842838),\n",
       "   ('jour', 0.0029852095),\n",
       "   ('jeune', 0.002953522),\n",
       "   ('pouvoir', 0.002634758),\n",
       "   ('ete', 0.0026221378),\n",
       "   ('place', 0.002578728),\n",
       "   ('voir', 0.002355145),\n",
       "   ('venir', 0.0023003346),\n",
       "   ('annee', 0.0022076827),\n",
       "   ('samedi', 0.0021554558),\n",
       "   ('marche', 0.0020674823),\n",
       "   ('ecole', 0.0020520668)]),\n",
       " (4,\n",
       "  [('enfant', 0.005562502),\n",
       "   ('jeune', 0.0029422825),\n",
       "   ('personnage', 0.0027490873),\n",
       "   ('voir', 0.0026907208),\n",
       "   ('prendre', 0.0024717827),\n",
       "   ('devenir', 0.0023233695),\n",
       "   ('vie', 0.0023077994),\n",
       "   ('fois', 0.0022404105),\n",
       "   ('pouvoir', 0.002159338),\n",
       "   ('annee', 0.002157877),\n",
       "   ('aventure', 0.0021378803),\n",
       "   ('titre', 0.0020047326),\n",
       "   ('ecran', 0.001981349),\n",
       "   ('film', 0.0019532475),\n",
       "   ('art', 0.0018719815)]),\n",
       " (5,\n",
       "  [('jeune', 0.0058422093),\n",
       "   ('enfant', 0.005512665),\n",
       "   ('violence', 0.004104295),\n",
       "   ('film', 0.0037244768),\n",
       "   ('parent', 0.0031563158),\n",
       "   ('voir', 0.0027765294),\n",
       "   ('pouvoir', 0.0025996517),\n",
       "   ('sport', 0.0025031886),\n",
       "   ('ete', 0.0024807989),\n",
       "   ('eleve', 0.0024705),\n",
       "   ('annee', 0.0024310038),\n",
       "   ('vouloir', 0.0022814393),\n",
       "   ('prendre', 0.0022543008),\n",
       "   ('savoir', 0.0022019066),\n",
       "   ('jour', 0.0021135733)]),\n",
       " (6,\n",
       "  [('jeune', 0.0064091017),\n",
       "   ('million', 0.0029589403),\n",
       "   ('ete', 0.002727101),\n",
       "   ('franc', 0.0026197196),\n",
       "   ('enfant', 0.0026193797),\n",
       "   ('suisse', 0.0025498986),\n",
       "   ('conseil', 0.0024313033),\n",
       "   ('heure', 0.002338809),\n",
       "   ('jour', 0.002297812),\n",
       "   ('prendre', 0.002257031),\n",
       "   ('fonds', 0.0022337413),\n",
       "   ('vouloir', 0.002192919),\n",
       "   ('mois', 0.0021800406),\n",
       "   ('groupe', 0.0020735185),\n",
       "   ('centre', 0.0019998646)]),\n",
       " (7,\n",
       "  [('million', 0.0040726503),\n",
       "   ('annee', 0.0036304921),\n",
       "   ('marche', 0.0034714176),\n",
       "   ('ete', 0.003066973),\n",
       "   ('suisse', 0.0029601064),\n",
       "   ('franc', 0.0027297188),\n",
       "   ('image', 0.0025666296),\n",
       "   ('societe', 0.0025579224),\n",
       "   ('etat', 0.0025517736),\n",
       "   ('vente', 0.0024240946),\n",
       "   ('americain', 0.0022996957),\n",
       "   ('console', 0.002252194),\n",
       "   ('television', 0.0022486292),\n",
       "   ('guerre', 0.0020369112),\n",
       "   ('ordinateur', 0.002025187)]),\n",
       " (8,\n",
       "  [('console', 0.005694737),\n",
       "   ('nintendo', 0.005263297),\n",
       "   ('titre', 0.004574303),\n",
       "   ('mode', 0.004493244),\n",
       "   ('playstation', 0.0033150613),\n",
       "   ('niveau', 0.002959319),\n",
       "   ('course', 0.0026983172),\n",
       "   ('aventure', 0.0026007432),\n",
       "   ('version', 0.0025159926),\n",
       "   ('personnage', 0.0024549218),\n",
       "   ('main', 0.0023583942),\n",
       "   ('arme', 0.0023125086),\n",
       "   ('mario', 0.0023052872),\n",
       "   ('prendre', 0.0022993337),\n",
       "   ('propose', 0.0022833028)])]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lda_model.show_topics(formatted=False, num_words = 15, num_topics=9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "id": "b781f13b-5210-4e97-8a71-0a8476fcfcbc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>words</th>\n",
       "      <th>brief</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>[console, nintendo, playstation, sony, machine...</td>\n",
       "      <td>consoles playstation nintendo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[pouvoir, film, console, combat, propose, ecra...</td>\n",
       "      <td>\"VideoGames&amp;Cinema1\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[film, jeune, suisse, course, mode, histoire, ...</td>\n",
       "      <td>\"VideoGames&amp;Cinema2\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[enfant, film, suisse, heure, jour, jeune, pou...</td>\n",
       "      <td>children school young time</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[enfant, jeune, personnage, voir, prendre, dev...</td>\n",
       "      <td>\"Education\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[jeune, enfant, violence, film, parent, voir, ...</td>\n",
       "      <td>\"Violence\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[jeune, million, ete, franc, enfant, suisse, c...</td>\n",
       "      <td>\"Politics\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[million, annee, marche, ete, suisse, franc, i...</td>\n",
       "      <td>\"Economics\"</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>[console, nintendo, titre, mode, playstation, ...</td>\n",
       "      <td>\"Game news\"</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                               words  \\\n",
       "0  [console, nintendo, playstation, sony, machine...   \n",
       "1  [pouvoir, film, console, combat, propose, ecra...   \n",
       "2  [film, jeune, suisse, course, mode, histoire, ...   \n",
       "3  [enfant, film, suisse, heure, jour, jeune, pou...   \n",
       "4  [enfant, jeune, personnage, voir, prendre, dev...   \n",
       "5  [jeune, enfant, violence, film, parent, voir, ...   \n",
       "6  [jeune, million, ete, franc, enfant, suisse, c...   \n",
       "7  [million, annee, marche, ete, suisse, franc, i...   \n",
       "8  [console, nintendo, titre, mode, playstation, ...   \n",
       "\n",
       "                           brief  \n",
       "0  consoles playstation nintendo  \n",
       "1           \"VideoGames&Cinema1\"  \n",
       "2           \"VideoGames&Cinema2\"  \n",
       "3     children school young time  \n",
       "4                    \"Education\"  \n",
       "5                     \"Violence\"  \n",
       "6                     \"Politics\"  \n",
       "7                    \"Economics\"  \n",
       "8                    \"Game news\"  "
      ]
     },
     "execution_count": 108,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create a dataframe with the top 15 words for each topic and a brief description for each one\n",
    "words = []\n",
    "for topic in lda_model.show_topics(formatted=False, num_words = 15, num_topics=15):\n",
    "    temp = []\n",
    "    for (word, prob) in topic[1]:\n",
    "        temp.append(word)\n",
    "    words.append(temp)\n",
    "words\n",
    "    \n",
    "# Those briefs are either a subset of the words assigned to the topic, or come from the analysis\n",
    "# which is beign performed at the end of this notebook, which we used to then rename those categories\n",
    "brief = ['consoles playstation nintendo', '\"VideoGames&Cinema1\"', '\"VideoGames&Cinema2\"', \n",
    "         'children school young time', '\"Education\"', '\"Violence\"', '\"Politics\"',  \n",
    "         '\"Economics\"', '\"Game news\"']\n",
    "\n",
    "topic_df = pd.DataFrame(list(zip(words,brief)), columns=['words','brief'])\n",
    "topic_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "id": "ea45421b-92ec-4bf3-b105-4eafd7386b78",
   "metadata": {},
   "outputs": [],
   "source": [
    "# For each document get which topic it probably belongs to\n",
    "article_topics = []\n",
    "for i, doc in enumerate(data):\n",
    "    bow = dictionary.doc2bow(doc)\n",
    "    doc_topics, word_topics, phi_values = lda_model.get_document_topics(\n",
    "        bow, per_word_topics = True)\n",
    "    article_topics.append(doc_topics)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "e507b9ee-a483-4039-a16f-56a297661a37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>article</th>\n",
       "      <th>topics</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Un jour en Suisse \" sera insuffisant pour déco...</td>\n",
       "      <td>[(1, 0.11784285), (2, 0.025124976), (3, 0.1007...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Après une campagne de protestation 500 000 vis...</td>\n",
       "      <td>[(5, 0.24079965), (6, 0.37143046), (7, 0.35921...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Â Bâle, la formation professionnelle horlogère...</td>\n",
       "      <td>[(3, 0.82927465), (4, 0.013119309), (6, 0.0675...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Stand «Formation professionnelle horlogère » à...</td>\n",
       "      <td>[(3, 0.8345946), (4, 0.022407984), (6, 0.04952...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Luciano Berio à Genève Peter Maag à Zurich et ...</td>\n",
       "      <td>[(1, 0.06794338), (2, 0.26038378), (3, 0.30930...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             article  \\\n",
       "0  Un jour en Suisse \" sera insuffisant pour déco...   \n",
       "1  Après une campagne de protestation 500 000 vis...   \n",
       "2  Â Bâle, la formation professionnelle horlogère...   \n",
       "3  Stand «Formation professionnelle horlogère » à...   \n",
       "4  Luciano Berio à Genève Peter Maag à Zurich et ...   \n",
       "\n",
       "                                              topics  \n",
       "0  [(1, 0.11784285), (2, 0.025124976), (3, 0.1007...  \n",
       "1  [(5, 0.24079965), (6, 0.37143046), (7, 0.35921...  \n",
       "2  [(3, 0.82927465), (4, 0.013119309), (6, 0.0675...  \n",
       "3  [(3, 0.8345946), (4, 0.022407984), (6, 0.04952...  \n",
       "4  [(1, 0.06794338), (2, 0.26038378), (3, 0.30930...  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "classified = pd.DataFrame({'article': df.content, 'topics': article_topics})\n",
    "classified.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "c46bbe95-7c16-453c-b2ce-8daf8d8e0f3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the assigned topics for each article\n",
    "assigned_topics = []\n",
    "for probs in classified.topics:\n",
    "    temp = []\n",
    "    for (t, p) in probs:\n",
    "        temp.append(t)\n",
    "    assigned_topics.append(temp)\n",
    "classified['assigned_topics'] = assigned_topics\n",
    "classified['year'] = df.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "d61f7825-2d05-4d26-b320-1fc45d7f66cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>assigned_topics</th>\n",
       "      <th>year</th>\n",
       "      <th>topic0</th>\n",
       "      <th>topic1</th>\n",
       "      <th>topic2</th>\n",
       "      <th>topic3</th>\n",
       "      <th>topic4</th>\n",
       "      <th>topic5</th>\n",
       "      <th>topic6</th>\n",
       "      <th>topic7</th>\n",
       "      <th>topic8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Un jour en Suisse \" sera insuffisant pour déco...</td>\n",
       "      <td>[(1, 0.11784285), (2, 0.025124976), (3, 0.1007...</td>\n",
       "      <td>[1, 2, 3, 4, 5, 6, 7, 8]</td>\n",
       "      <td>1964</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Après une campagne de protestation 500 000 vis...</td>\n",
       "      <td>[(5, 0.24079965), (6, 0.37143046), (7, 0.35921...</td>\n",
       "      <td>[5, 6, 7, 8]</td>\n",
       "      <td>1964</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Â Bâle, la formation professionnelle horlogère...</td>\n",
       "      <td>[(3, 0.82927465), (4, 0.013119309), (6, 0.0675...</td>\n",
       "      <td>[3, 4, 6, 7]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Stand «Formation professionnelle horlogère » à...</td>\n",
       "      <td>[(3, 0.8345946), (4, 0.022407984), (6, 0.04952...</td>\n",
       "      <td>[3, 4, 6, 7]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Luciano Berio à Genève Peter Maag à Zurich et ...</td>\n",
       "      <td>[(1, 0.06794338), (2, 0.26038378), (3, 0.30930...</td>\n",
       "      <td>[1, 2, 3, 4, 5, 6]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             article  \\\n",
       "0  Un jour en Suisse \" sera insuffisant pour déco...   \n",
       "1  Après une campagne de protestation 500 000 vis...   \n",
       "2  Â Bâle, la formation professionnelle horlogère...   \n",
       "3  Stand «Formation professionnelle horlogère » à...   \n",
       "4  Luciano Berio à Genève Peter Maag à Zurich et ...   \n",
       "\n",
       "                                              topics  \\\n",
       "0  [(1, 0.11784285), (2, 0.025124976), (3, 0.1007...   \n",
       "1  [(5, 0.24079965), (6, 0.37143046), (7, 0.35921...   \n",
       "2  [(3, 0.82927465), (4, 0.013119309), (6, 0.0675...   \n",
       "3  [(3, 0.8345946), (4, 0.022407984), (6, 0.04952...   \n",
       "4  [(1, 0.06794338), (2, 0.26038378), (3, 0.30930...   \n",
       "\n",
       "            assigned_topics  year  topic0  topic1  topic2  topic3  topic4  \\\n",
       "0  [1, 2, 3, 4, 5, 6, 7, 8]  1964     0.0     1.0     1.0     1.0     1.0   \n",
       "1              [5, 6, 7, 8]  1964     0.0     0.0     0.0     0.0     0.0   \n",
       "2              [3, 4, 6, 7]  1970     0.0     0.0     0.0     1.0     1.0   \n",
       "3              [3, 4, 6, 7]  1970     0.0     0.0     0.0     1.0     1.0   \n",
       "4        [1, 2, 3, 4, 5, 6]  1970     0.0     1.0     1.0     1.0     1.0   \n",
       "\n",
       "   topic5  topic6  topic7  topic8  \n",
       "0     1.0     1.0     1.0     1.0  \n",
       "1     1.0     1.0     1.0     1.0  \n",
       "2     0.0     1.0     1.0     0.0  \n",
       "3     0.0     1.0     1.0     0.0  \n",
       "4     1.0     1.0     0.0     0.0  "
      ]
     },
     "execution_count": 111,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create one hot vectors for each article and topic (1 if the topic is in the article's distribution, 0 if not)\n",
    "one_hots = []\n",
    "\n",
    "for probs in classified.topics:\n",
    "    onehot = np.zeros(9)\n",
    "    for (t, p) in probs:\n",
    "        onehot[t] = 1\n",
    "    one_hots.append(onehot)\n",
    "one_hots\n",
    "one_hot_matrix = np.stack(one_hots, axis=1)\n",
    "for i in range(9):\n",
    "    classified[\"topic{}\".format(i)] = one_hot_matrix[i]\n",
    "classified.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "2bfa6cac-6aaa-4a68-9365-02c1a84dfe34",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>article</th>\n",
       "      <th>topics</th>\n",
       "      <th>assigned_topics</th>\n",
       "      <th>year</th>\n",
       "      <th>topic0</th>\n",
       "      <th>topic1</th>\n",
       "      <th>topic2</th>\n",
       "      <th>topic3</th>\n",
       "      <th>topic4</th>\n",
       "      <th>topic5</th>\n",
       "      <th>topic6</th>\n",
       "      <th>topic7</th>\n",
       "      <th>topic8</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Un jour en Suisse \" sera insuffisant pour déco...</td>\n",
       "      <td>[(1, 0.11784285), (2, 0.025124976), (3, 0.1007...</td>\n",
       "      <td>[1, 2, 3, 4, 5, 6, 7, 8]</td>\n",
       "      <td>1964</td>\n",
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       "      <td>0.100777</td>\n",
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       "      <td>0.079224</td>\n",
       "      <td>0.292907</td>\n",
       "      <td>0.240291</td>\n",
       "      <td>0.041138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Après une campagne de protestation 500 000 vis...</td>\n",
       "      <td>[(5, 0.24079965), (6, 0.37143046), (7, 0.35921...</td>\n",
       "      <td>[5, 6, 7, 8]</td>\n",
       "      <td>1964</td>\n",
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       "      <td>0.240800</td>\n",
       "      <td>0.371430</td>\n",
       "      <td>0.359216</td>\n",
       "      <td>0.027003</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Â Bâle, la formation professionnelle horlogère...</td>\n",
       "      <td>[(3, 0.82927465), (4, 0.013119309), (6, 0.0675...</td>\n",
       "      <td>[3, 4, 6, 7]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.829275</td>\n",
       "      <td>0.013119</td>\n",
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       "      <td>0.067531</td>\n",
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       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Stand «Formation professionnelle horlogère » à...</td>\n",
       "      <td>[(3, 0.8345946), (4, 0.022407984), (6, 0.04952...</td>\n",
       "      <td>[3, 4, 6, 7]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.834595</td>\n",
       "      <td>0.022408</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.049525</td>\n",
       "      <td>0.091877</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Luciano Berio à Genève Peter Maag à Zurich et ...</td>\n",
       "      <td>[(1, 0.06794338), (2, 0.26038378), (3, 0.30930...</td>\n",
       "      <td>[1, 2, 3, 4, 5, 6]</td>\n",
       "      <td>1970</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.067943</td>\n",
       "      <td>0.260384</td>\n",
       "      <td>0.309304</td>\n",
       "      <td>0.195582</td>\n",
       "      <td>0.129083</td>\n",
       "      <td>0.037422</td>\n",
       "      <td>0.000000</td>\n",
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      "text/plain": [
       "                                             article  \\\n",
       "0  Un jour en Suisse \" sera insuffisant pour déco...   \n",
       "1  Après une campagne de protestation 500 000 vis...   \n",
       "2  Â Bâle, la formation professionnelle horlogère...   \n",
       "3  Stand «Formation professionnelle horlogère » à...   \n",
       "4  Luciano Berio à Genève Peter Maag à Zurich et ...   \n",
       "\n",
       "                                              topics  \\\n",
       "0  [(1, 0.11784285), (2, 0.025124976), (3, 0.1007...   \n",
       "1  [(5, 0.24079965), (6, 0.37143046), (7, 0.35921...   \n",
       "2  [(3, 0.82927465), (4, 0.013119309), (6, 0.0675...   \n",
       "3  [(3, 0.8345946), (4, 0.022407984), (6, 0.04952...   \n",
       "4  [(1, 0.06794338), (2, 0.26038378), (3, 0.30930...   \n",
       "\n",
       "            assigned_topics  year  topic0    topic1    topic2    topic3  \\\n",
       "0  [1, 2, 3, 4, 5, 6, 7, 8]  1964     0.0  0.117843  0.025125  0.100777   \n",
       "1              [5, 6, 7, 8]  1964     0.0  0.000000  0.000000  0.000000   \n",
       "2              [3, 4, 6, 7]  1970     0.0  0.000000  0.000000  0.829275   \n",
       "3              [3, 4, 6, 7]  1970     0.0  0.000000  0.000000  0.834595   \n",
       "4        [1, 2, 3, 4, 5, 6]  1970     0.0  0.067943  0.260384  0.309304   \n",
       "\n",
       "     topic4    topic5    topic6    topic7    topic8  \n",
       "0  0.102580  0.079224  0.292907  0.240291  0.041138  \n",
       "1  0.000000  0.240800  0.371430  0.359216  0.027003  \n",
       "2  0.013119  0.000000  0.067531  0.088546  0.000000  \n",
       "3  0.022408  0.000000  0.049525  0.091877  0.000000  \n",
       "4  0.195582  0.129083  0.037422  0.000000  0.000000  "
      ]
     },
     "execution_count": 112,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Instead of assigning each topic for a document 1.0, assign it the probability that LDA outputs\n",
    "classified2 = classified.drop(['topic0', 'topic1', 'topic2', 'topic3', 'topic4', 'topic5', 'topic6', 'topic7', 'topic8'], axis=1)\n",
    "classified2\n",
    "\n",
    "one_hots = []\n",
    "for probs in classified2.topics:\n",
    "    onehot = np.zeros(9)\n",
    "    for (t, p) in probs:\n",
    "        onehot[t] = p\n",
    "    one_hots.append(onehot)\n",
    "one_hots\n",
    "one_hot_matrix = np.stack(one_hots, axis=1)\n",
    "for i in range(9):\n",
    "    classified2[\"topic{}\".format(i)] = one_hot_matrix[i]\n",
    "classified2.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "509cb66e-f4d7-454d-9e85-ebb3e161b428",
   "metadata": {},
   "source": [
    "### Visualize Topics over Time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "622b366e-b24d-45c4-914d-d741ac71d118",
   "metadata": {},
   "outputs": [],
   "source": [
    "def setup_year_axis_plt():\n",
    "    plt.xlabel(\"Year\")\n",
    "    plt.xlim(1960, 2019)\n",
    "    plt.xticks([1964, 1970, 1980, 1990, 2000, 2018])\n",
    "    \n",
    "def setup_year_axis(ax):\n",
    "    ax.set_xlabel(\"Year\")\n",
    "    ax.set_xlim(1960, 2019)\n",
    "    ax.set_xticks([1964, 1970, 1980, 1990, 2000, 2018])\n",
    "\n",
    "yearcounts = df['year'].value_counts()\n",
    "\n",
    "# Selected topics from the human analysis\n",
    "topics_of_interest = [4, 5, 6, 7, 8]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "3dd5aed6-eb12-49d0-b0b0-3ca523f530cc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at the number of articles mentioning each topic on one plot\n",
    "for i in topics_of_interest:\n",
    "    grouped = classified[['year', 'topic{}'.format(i)]].groupby('year').sum()\n",
    "    grouped['total_per_yr'] = yearcounts[grouped.index]\n",
    "    plt.plot(grouped.index, grouped['topic{}'.format(i)], label = topic_df.iloc[i].brief)\n",
    "    plt.title(\"Evolution of Topics\")\n",
    "    setup_year_axis_plt()\n",
    "    plt.ylabel(\"Number of Articles Mentioning Each Topic\".format(i))\n",
    "    plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "7d259df1-c3b3-426e-9ebd-f9f9eebeccdd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at the number of articles mentioning each topic on one plot\n",
    "# probability version (looks pretty similar)\n",
    "for i in topics_of_interest:\n",
    "    grouped = classified2[['year', 'topic{}'.format(i)]].groupby('year').sum()\n",
    "    grouped['total_per_yr'] = yearcounts[grouped.index]\n",
    "    plt.plot(grouped.index, grouped['topic{}'.format(i)], label = topic_df.iloc[i].brief)\n",
    "    plt.title(\"Evolution of Topics\")\n",
    "    setup_year_axis_plt()\n",
    "    plt.ylabel(\"Sum of Document Topic Probabilities\".format(i))\n",
    "    plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e3a8e5a",
   "metadata": {},
   "source": [
    "One interesting thing about those two graphics:\n",
    "- They both have the exact same shape;\n",
    "- The second one has a bigger gap between the categories.\n",
    "\n",
    "This first point can be explained by the discrepancies in the number of articles per year, which will be come evident after doing the same plot with relative numbers.\n",
    "\n",
    "The second point seems to hint that there are topics where the model is way more confident in its assignment, since it consistently assigns higher probabilities throughout the years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "c13b23ce-22c2-4a82-91ea-d53b8f3f1ba1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at the proportion of articles mentioning each topic\n",
    "for i in topics_of_interest:\n",
    "    grouped = classified[['year', 'topic{}'.format(i)]].groupby('year').sum()\n",
    "    grouped['total_per_yr'] = yearcounts[grouped.index]\n",
    "    plt.plot(grouped.index, grouped['topic{}'.format(i)]/grouped.total_per_yr, label = topic_df.iloc[i].brief)\n",
    "    plt.title(\"Evolution of Topics\")\n",
    "    setup_year_axis_plt()\n",
    "    plt.ylabel(\"Proportion of Articles\".format(i))\n",
    "    plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "c9c388c0-e14f-4f27-bc5c-9bbc3dbfbbba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at the proportion of articles mentioning each topic\n",
    "# probability version\n",
    "for i in topics_of_interest:\n",
    "    grouped = classified2[['year', 'topic{}'.format(i)]].groupby('year').sum()\n",
    "    grouped['total_per_yr'] = yearcounts[grouped.index]\n",
    "    plt.plot(grouped.index, grouped['topic{}'.format(i)]/grouped.total_per_yr, label = topic_df.iloc[i].brief)\n",
    "    plt.title(\"Evolution of Topics\")\n",
    "    setup_year_axis_plt()\n",
    "    plt.ylabel(\"Proportion of Articles\".format(i))\n",
    "    plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "d48a517c-1674-4fff-b181-64366c067796",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1800 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Look at some of the more interesting topics\n",
    "# Might be best to choose the most interesting topics and make a figure because it's a bit confusing all on one\n",
    "# plot\n",
    "\n",
    "\n",
    "fig = plt.figure(figsize = (10, 5 * len(topics_of_interest)))\n",
    "\n",
    "for i, topic_id in enumerate(topics_of_interest):\n",
    "    grouped = classified[['year', 'topic{}'.format(topic_id)]].groupby('year').sum()\n",
    "    grouped['total_per_yr'] = yearcounts[grouped.index]\n",
    "\n",
    "    ax_abs = fig.add_subplot(len(topics_of_interest), 2, 2*i + 1)\n",
    "    ax_rel = fig.add_subplot(len(topics_of_interest), 2, 2*i + 2)\n",
    "\n",
    "\n",
    "    ax_abs.plot(grouped.index, grouped['topic{}'.format(topic_id)])\n",
    "    ax_abs.set_title(\"Evolution of Topic {}: {}\".format(topic_id, topic_df.iloc[topic_id].brief))\n",
    "    setup_year_axis(ax_abs)\n",
    "    ax_abs.set_ylabel(\"Number of Articles Mentioning Topic {}\".format(topic_id))\n",
    "\n",
    "    ax_rel.plot(grouped.index, grouped['topic{}'.format(topic_id)]/grouped.total_per_yr)\n",
    "    ax_rel.set_title(\"Evolution of Topic {}: {}\".format(topic_id, topic_df.iloc[topic_id].brief))\n",
    "    setup_year_axis(ax_rel)\n",
    "    ax_rel.set_ylabel(\"Proportion of Articles Mentioning Topic {}\".format(topic_id))\n",
    "    ax_rel.set_ylim(0.0, 1.0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe8ea9b9",
   "metadata": {},
   "source": [
    "The huge variations happening around 1964-1980 and around 2018 can be simply explained by the fact that there are really few articles in those periods, which implies that depending on a handful of assignments, the relative value can quickly jump to 1.0 or drop to 0.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "077cdf27-ee45-4baa-b534-b8cbafbac72a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 consoles playstation nintendo\n",
      "[(297, 0.39168602), (3889, 0.36431935), (820, 0.3564074), (177, 0.34271187), (451, 0.33584955)]\n",
      "1 film combat action mission\n",
      "[(2586, 0.49409467), (2585, 0.4940894), (2566, 0.48558393), (2565, 0.48558232), (199, 0.47322258)]\n",
      "2 film story car\n",
      "[(161, 0.78259623), (160, 0.7825951), (168, 0.5970634), (167, 0.5970617), (850, 0.53892654)]\n",
      "3 children school young time\n",
      "[(5, 0.88737065), (6, 0.8808923), (9, 0.8540933), (7, 0.8491672), (3, 0.8345734)]\n",
      "4 art film screen children\n",
      "[(16, 0.6404224), (3851, 0.6278196), (3850, 0.62385386), (1984, 0.6107961), (101, 0.55324817)]\n",
      "5 violence\n",
      "[(23, 0.57609284), (21, 0.5554249), (22, 0.55542135), (65, 0.5009943), (3328, 0.46463355)]\n",
      "6 money funds\n",
      "[(12, 0.74919695), (13, 0.74768645), (684, 0.5547808), (41, 0.55049324), (45, 0.52190125)]\n",
      "7 money image american television\n",
      "[(95, 0.71995234), (94, 0.7199514), (3880, 0.5832964), (141, 0.57769907), (52, 0.5625465)]\n",
      "8 consoles playstation sony nintendo controller gun\n",
      "[(1007, 0.58140945), (1013, 0.50815374), (3701, 0.47527364), (4318, 0.4398015), (4317, 0.43978855)]\n"
     ]
    }
   ],
   "source": [
    "min_text_len = 500 # Only keep longer articles, which are more interesting to analyze\n",
    "keep_count = 5 # Number of articles to display\n",
    "\n",
    "# Create a dictionary grouping the probabilities for each topic\n",
    "topic_dict = {i: [] for i in range(9)} \n",
    "\n",
    "for docID in range(len(df.content)):\n",
    "    topic_vector = lda_model[corpus[docID]]\n",
    "    \n",
    "    \n",
    "    if len(df.content[docID]) > min_text_len:\n",
    "        for topic, prob in topic_vector:\n",
    "            topic_dict[topic].append((docID, prob))\n",
    "\n",
    "# Sort the dictionary to find the top n document ids for each topic\n",
    "for topic, probs in topic_dict.items():\n",
    "    doc_probs = sorted(probs, key = lambda x: x[1], reverse = True)\n",
    "    docs_top = [dp for dp in doc_probs[:keep_count]] \n",
    "    print(topic, brief[topic])\n",
    "    print(docs_top)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "952dcc3f",
   "metadata": {},
   "source": [
    "With human intervention, it is possible to analyze those top documents to find a better label to the topic group:\n",
    "\n",
    "0. No real link we could observe\n",
    "1. Seems to link video-games with cinema (mostly articles)\n",
    "2. Seems to link video-games with cinema (mostly annoucements about film related to videogames)\n",
    "3. Always the same article (thanks impresso) about using videogames to teach watchmaking.\n",
    "4. Education\n",
    "5. Violence, but not in an expected way: \"Battleships\" and ISIS\n",
    "6. Mostly \"politic-related\" stuff\n",
    "7. Strong connection to economics; video games are usually just mentionned (funny to see they thought it was reaching its peak)\n",
    "8. Mostly informations about the new games"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "d7c779d3-490f-4711-b952-0dfe64ec986f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "uid                                                       IMP-1996-11-06-a-i0151\n",
      "type                                                                         NaN\n",
      "language                                                                      fr\n",
      "title                                Jeux vidéo Après «Wipe Out» «Wipe Out 2097»\n",
      "size                                                                         178\n",
      "country                                                                       CH\n",
      "newspaper                                                                    IMP\n",
      "issue                                                           IMP-1996-11-06-a\n",
      "pages                                                                         17\n",
      "nb_pages                                                                       1\n",
      "relevance                                                                    0.0\n",
      "year                                                                        1996\n",
      "is_on_front                                                                False\n",
      "date                                                   1996-11-06 00:00:00+00:00\n",
      "persons_mentioned                                                 Pascal Tissier\n",
      "locations_mentioned                                                          NaN\n",
      "content                        Jeux vidéo Après « Wipe Out » « Wipe Out 2097 ...\n",
      "access_right                                                         OpenPrivate\n",
      "content_provider                                                             SNL\n",
      "is_content_available                                                           y\n",
      "[total:7120,available:7200]                                                  NaN\n",
      "Name: 1007, dtype: object\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"Jeux vidéo Après « Wipe Out » « Wipe Out 2097 » Si « Wipe Out », l'un des premiers jeux de la Playstation, n'était pas nouveau, ses graphismes, lors de sa sortie, avaient fait sensation et avaient ouverts les portes du succès à la console de Sony. Aujourd'hui, la nouvelle version de ce jeu d'enfer vient de sortir : « Wipe Out 2097 », ou comment on fait du neuf avec du vieux. Un jeu où l'on s'en donne à coeur joie dans des simulations de courses futuristes, un jeu dont l'innovation la plus marquante, en course, est l'apparition d'une harre d'énergie qui se vide dangereusement lors d'impacts ou de chocs. L'aspect graphique de l'ensemble a été complètement revu et amélioré. A en croire notre spécialiste de la console, Pascal Tissier, « Wipe Out » nouvelle formule procure déjà des sensations fortes après quelques minutes d'entraînement seulement. Et quand la piste se met à onduler, il faut vraiment s'accrocher ! _ _ p 25 « Wipe Out 2097 » comblera tous les amateurs de vitesse. Photo Psygnosis \""
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# can look at the most representative documents for each topic\n",
    "idx = 1007\n",
    "print(df.iloc[idx])\n",
    "df.content[idx]"
   ]
  }
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