{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "305b0a04",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "from pprint import pprint\n",
    "from nltk.corpus import stopwords\n",
    "from gensim.utils import simple_preprocess\n",
    "from gensim.models import Phrases, LdaModel\n",
    "from gensim.models.phrases import Phraser\n",
    "from gensim import corpora\n",
    "from gensim.models.coherencemodel import CoherenceModel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b44f0e77",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package stopwords to\n",
      "[nltk_data]     C:\\Users\\vldth\\AppData\\Roaming\\nltk_data...\n",
      "[nltk_data]   Package stopwords is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import nltk\n",
    "nltk.download('stopwords')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "20eb23e6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Original dataset:\n",
      "                                              review  sentiment\n",
      "0  at first gumagana cya..pero pagnalowbat cya nd...          1\n",
      "1  grabi pangalawa ko ng order sa shapee pero pur...          1\n",
      "2  2l gray/black order ko. bakit 850ml lang po pi...          1\n",
      "3  walang silbing product.. bwesit. di gumagana d...          1\n",
      "4  d po maganda naman po yung neck fan, pero po n...          4\n"
     ]
    }
   ],
   "source": [
    "# Load the dataset\n",
    "df = pd.read_csv('SentiTaglish_ProductsAndServices.csv')\n",
    "print(\"Original dataset:\")\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "04ac2df1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                                              review\n",
      "0  at first gumagana cya..pero pagnalowbat cya nd...\n",
      "1  grabi pangalawa ko ng order sa shapee pero pur...\n",
      "2  2l gray/black order ko. bakit 850ml lang po pi...\n",
      "3  walang silbing product.. bwesit. di gumagana d...\n",
      "4  d po maganda naman po yung neck fan, pero po n...\n"
     ]
    }
   ],
   "source": [
    "# Drop the sentiment column\n",
    "reviews_df = df.drop(columns=['sentiment'])\n",
    "print(reviews_df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "4ec261ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "documents = reviews_df['review'].astype(str).tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "001e98d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "#load tagalog stopwords function\n",
    "def load_stopwords(filepath):\n",
    "    with open(filepath, 'r', encoding='utf-8') as file:\n",
    "        return set(line.strip() for line in file if line.strip())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "01e67728",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define stopwords\n",
    "english_stopwords = stopwords.words('english')\n",
    "\n",
    "# Tagalog/Filipino stopwords \n",
    "tagalog_stopwords = load_stopwords(\"stopwords-new.txt\")\n",
    "\n",
    "combined_stopwords = set(english_stopwords).union(tagalog_stopwords)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "215e29fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Preprocessing function\n",
    "def preprocess_data(documents):\n",
    "    return [\n",
    "        [word for word in simple_preprocess(str(doc)) if word not in combined_stopwords]\n",
    "        for doc in documents\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "b3c0885c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 1. Preprocess and tokenize your documents\n",
    "processed_texts = preprocess_data(documents)  # Should return list of tokenized docs\n",
    "\n",
    "# 2. Create bigram and trigram models\n",
    "bigram = Phrases(processed_texts, min_count=3, threshold=5)\n",
    "trigram = Phrases(bigram[processed_texts], threshold=5)\n",
    "\n",
    "# 3. Convert to efficient Phrasers\n",
    "bigram_mod = Phraser(bigram)\n",
    "trigram_mod = Phraser(trigram)\n",
    "\n",
    "# 4. Apply phrase models\n",
    "def make_ngrams(texts):\n",
    "    bigram_texts = [bigram_mod[doc] for doc in texts]\n",
    "    trigram_texts = [trigram_mod[doc] for doc in bigram_texts]\n",
    "    return trigram_texts\n",
    "\n",
    "ngrammed_texts = make_ngrams(processed_texts)\n",
    "\n",
    "# 5. Join tokens back into strings\n",
    "texts_for_bertopic = [' '.join(doc) for doc in ngrammed_texts]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f6f4f0b1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BERTopic is working!\n"
     ]
    }
   ],
   "source": [
    "from bertopic import BERTopic\n",
    "print(\"BERTopic is working!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "9ac0a678",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize BERTopic\n",
    "topic_model = BERTopic(language=\"multilingual\")\n",
    "\n",
    "# Fit the model on the preprocessed texts\n",
    "topics, probs = topic_model.fit_transform(texts_for_bertopic)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f0856aac",
   "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>Topic</th>\n",
       "      <th>Count</th>\n",
       "      <th>Name</th>\n",
       "      <th>Representation</th>\n",
       "      <th>Representative_Docs</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1</td>\n",
       "      <td>3614</td>\n",
       "      <td>-1_item_seller_product_kasi</td>\n",
       "      <td>[item, seller, product, kasi, order, maganda, ...</td>\n",
       "      <td>[maganda mura thank order next_time, ganda ite...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0</td>\n",
       "      <td>993</td>\n",
       "      <td>0_color_black_white_pink</td>\n",
       "      <td>[color, black, white, pink, blue, green, wrong...</td>\n",
       "      <td>[disappointed wrong_color purple pink, pink_bl...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>514</td>\n",
       "      <td>1_size_maliit_size_sizes_add_size</td>\n",
       "      <td>[size, maliit_size, sizes, add_size, maliit, l...</td>\n",
       "      <td>[wrong_size binigay order size size binigay, c...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>463</td>\n",
       "      <td>2_dumating_sira_lng_ok</td>\n",
       "      <td>[dumating, sira, lng, ok, agad, sana, maganda,...</td>\n",
       "      <td>[sobrang nakakadismaya basta maka deliver lng ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3</td>\n",
       "      <td>336</td>\n",
       "      <td>3_price_worth_worth_price_good_price</td>\n",
       "      <td>[price, worth, worth_price, good_price, sakto_...</td>\n",
       "      <td>[maganda worth_price, ganda worth, okay lng pr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>4</td>\n",
       "      <td>194</td>\n",
       "      <td>4_food_place_masarap_service</td>\n",
       "      <td>[food, place, masarap, service, staff, rice, c...</td>\n",
       "      <td>[service good energy crew poor took mins food ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5</td>\n",
       "      <td>181</td>\n",
       "      <td>5_order_shop_thank_seller_order_received</td>\n",
       "      <td>[order, shop, thank_seller, order_received, or...</td>\n",
       "      <td>[goods order_received maganda gumagana thank_s...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>6</td>\n",
       "      <td>175</td>\n",
       "      <td>6_damage_item_damaged_items</td>\n",
       "      <td>[damage, item, damaged, items, box, product, t...</td>\n",
       "      <td>[ganda damage thankyou_seller, damage dumating...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>7</td>\n",
       "      <td>158</td>\n",
       "      <td>7_good_quality_good_maganda_quality_quality</td>\n",
       "      <td>[good_quality, good, maganda_quality, quality,...</td>\n",
       "      <td>[good_quality ganda, good_quality, maganda goo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>8</td>\n",
       "      <td>156</td>\n",
       "      <td>8_shoes_sandals_socks_boots</td>\n",
       "      <td>[shoes, sandals, socks, boots, slippers, legs,...</td>\n",
       "      <td>[maganda shoes price see_get, maganda shoes se...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>9</td>\n",
       "      <td>141</td>\n",
       "      <td>9_rider_ganda_ganda_kuya_rider_thank_seller</td>\n",
       "      <td>[rider, ganda_ganda, kuya_rider, thank_seller,...</td>\n",
       "      <td>[sakto thanks_seller rider well_packaged, than...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>10</td>\n",
       "      <td>132</td>\n",
       "      <td>10_bubble_wrap_naka_bubble_wrap_box_fragile</td>\n",
       "      <td>[bubble_wrap, naka_bubble_wrap, box, fragile, ...</td>\n",
       "      <td>[requested bubble_wrap nasa plastic buti nasir...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>11</td>\n",
       "      <td>129</td>\n",
       "      <td>11_order_order_ulit_nd_order_order_received</td>\n",
       "      <td>[order, order_ulit, nd_order, order_received, ...</td>\n",
       "      <td>[poor nasunod order st try mali agad wag_umord...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>12</td>\n",
       "      <td>108</td>\n",
       "      <td>12_refund_return_sayang_pera_return_refund</td>\n",
       "      <td>[refund, return, sayang_pera, return_refund, p...</td>\n",
       "      <td>[good dumating sira dami process refund, nakak...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>13</td>\n",
       "      <td>106</td>\n",
       "      <td>13_battery_rechargeable_battery_life_gumagana</td>\n",
       "      <td>[battery, rechargeable, battery_life, gumagana...</td>\n",
       "      <td>[kwenta gumagana bumili bagong battery everead...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>14</td>\n",
       "      <td>96</td>\n",
       "      <td>14_super_ganda_love_super_love_super</td>\n",
       "      <td>[super_ganda, love, super_love, super, love_th...</td>\n",
       "      <td>[see_get super_ganda talaga, legit super_ganda...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>15</td>\n",
       "      <td>94</td>\n",
       "      <td>15_scent_perfume_smell_amoy</td>\n",
       "      <td>[scent, perfume, smell, amoy, cloud, coconut, ...</td>\n",
       "      <td>[sure anong smell perfume toh disappointed, wa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>16</td>\n",
       "      <td>93</td>\n",
       "      <td>16_god_bless_godbless_maraming_salamat_merry_c...</td>\n",
       "      <td>[god_bless, godbless, maraming_salamat, merry_...</td>\n",
       "      <td>[good maraming_salamat sayo seller ganda item ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>17</td>\n",
       "      <td>91</td>\n",
       "      <td>17_sound_sounds_mic_sound_quality</td>\n",
       "      <td>[sound, sounds, mic, sound_quality, basag, aud...</td>\n",
       "      <td>[basag sounds case, basag sound mic sira paran...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>18</td>\n",
       "      <td>85</td>\n",
       "      <td>18_mascara_lipstick_lashes_eyeliner</td>\n",
       "      <td>[mascara, lipstick, lashes, eyeliner, lips, dr...</td>\n",
       "      <td>[mascara nice tho hold curl lashes curl lashes...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    Topic  Count                                               Name  \\\n",
       "0      -1   3614                        -1_item_seller_product_kasi   \n",
       "1       0    993                           0_color_black_white_pink   \n",
       "2       1    514                  1_size_maliit_size_sizes_add_size   \n",
       "3       2    463                             2_dumating_sira_lng_ok   \n",
       "4       3    336               3_price_worth_worth_price_good_price   \n",
       "5       4    194                       4_food_place_masarap_service   \n",
       "6       5    181           5_order_shop_thank_seller_order_received   \n",
       "7       6    175                        6_damage_item_damaged_items   \n",
       "8       7    158        7_good_quality_good_maganda_quality_quality   \n",
       "9       8    156                        8_shoes_sandals_socks_boots   \n",
       "10      9    141        9_rider_ganda_ganda_kuya_rider_thank_seller   \n",
       "11     10    132        10_bubble_wrap_naka_bubble_wrap_box_fragile   \n",
       "12     11    129        11_order_order_ulit_nd_order_order_received   \n",
       "13     12    108         12_refund_return_sayang_pera_return_refund   \n",
       "14     13    106      13_battery_rechargeable_battery_life_gumagana   \n",
       "15     14     96               14_super_ganda_love_super_love_super   \n",
       "16     15     94                        15_scent_perfume_smell_amoy   \n",
       "17     16     93  16_god_bless_godbless_maraming_salamat_merry_c...   \n",
       "18     17     91                  17_sound_sounds_mic_sound_quality   \n",
       "19     18     85                18_mascara_lipstick_lashes_eyeliner   \n",
       "\n",
       "                                       Representation  \\\n",
       "0   [item, seller, product, kasi, order, maganda, ...   \n",
       "1   [color, black, white, pink, blue, green, wrong...   \n",
       "2   [size, maliit_size, sizes, add_size, maliit, l...   \n",
       "3   [dumating, sira, lng, ok, agad, sana, maganda,...   \n",
       "4   [price, worth, worth_price, good_price, sakto_...   \n",
       "5   [food, place, masarap, service, staff, rice, c...   \n",
       "6   [order, shop, thank_seller, order_received, or...   \n",
       "7   [damage, item, damaged, items, box, product, t...   \n",
       "8   [good_quality, good, maganda_quality, quality,...   \n",
       "9   [shoes, sandals, socks, boots, slippers, legs,...   \n",
       "10  [rider, ganda_ganda, kuya_rider, thank_seller,...   \n",
       "11  [bubble_wrap, naka_bubble_wrap, box, fragile, ...   \n",
       "12  [order, order_ulit, nd_order, order_received, ...   \n",
       "13  [refund, return, sayang_pera, return_refund, p...   \n",
       "14  [battery, rechargeable, battery_life, gumagana...   \n",
       "15  [super_ganda, love, super_love, super, love_th...   \n",
       "16  [scent, perfume, smell, amoy, cloud, coconut, ...   \n",
       "17  [god_bless, godbless, maraming_salamat, merry_...   \n",
       "18  [sound, sounds, mic, sound_quality, basag, aud...   \n",
       "19  [mascara, lipstick, lashes, eyeliner, lips, dr...   \n",
       "\n",
       "                                  Representative_Docs  \n",
       "0   [maganda mura thank order next_time, ganda ite...  \n",
       "1   [disappointed wrong_color purple pink, pink_bl...  \n",
       "2   [wrong_size binigay order size size binigay, c...  \n",
       "3   [sobrang nakakadismaya basta maka deliver lng ...  \n",
       "4   [maganda worth_price, ganda worth, okay lng pr...  \n",
       "5   [service good energy crew poor took mins food ...  \n",
       "6   [goods order_received maganda gumagana thank_s...  \n",
       "7   [ganda damage thankyou_seller, damage dumating...  \n",
       "8   [good_quality ganda, good_quality, maganda goo...  \n",
       "9   [maganda shoes price see_get, maganda shoes se...  \n",
       "10  [sakto thanks_seller rider well_packaged, than...  \n",
       "11  [requested bubble_wrap nasa plastic buti nasir...  \n",
       "12  [poor nasunod order st try mali agad wag_umord...  \n",
       "13  [good dumating sira dami process refund, nakak...  \n",
       "14  [kwenta gumagana bumili bagong battery everead...  \n",
       "15  [see_get super_ganda talaga, legit super_ganda...  \n",
       "16  [sure anong smell perfume toh disappointed, wa...  \n",
       "17  [good maraming_salamat sayo seller ganda item ...  \n",
       "18  [basag sounds case, basag sound mic sira paran...  \n",
       "19  [mascara nice tho hold curl lashes curl lashes...  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "topic_info = topic_model.get_topic_info()\n",
    "display(topic_info.sort_values(by='Count', ascending=False).head(20))  # Top 20 topics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4d5acd76",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get and sort topics\n",
    "all_topics = topic_model.get_topic_info().sort_values(by='Count', ascending=False)\n",
    "\n",
    "# Style with borders, aligned text, and background gradient\n",
    "styled_html = all_topics.style.set_table_attributes('border=\"1\" class=\"dataframe\"') \\\n",
    "    .set_table_styles([\n",
    "        {'selector': 'th', 'props': [('border', '1px solid black'), ('background-color', '#f2f2f2'), ('padding', '8px')]},\n",
    "        {'selector': 'td', 'props': [('border', '1px solid black'), ('padding', '8px'), ('text-align', 'left')]},\n",
    "        {'selector': 'table', 'props': [('border-collapse', 'collapse'), ('width', '100%')]}\n",
    "    ]) \\\n",
    "    .background_gradient(subset=['Count'], cmap='Blues') \\\n",
    "    .set_properties(**{\n",
    "        'white-space': 'pre-wrap',\n",
    "        'text-align': 'left',\n",
    "    })\n",
    "\n",
    "# Save to HTML file\n",
    "styled_html.to_html(\"all_bertopic_topics.html\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9167d102",
   "metadata": {},
   "outputs": [
    {
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