notebooks/filtering/overlap_examination_Webis-TLDR-17_Reddit-TIFU_no_prior_filtering.ipynb

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   "metadata": {
    "id": "SNNl2N6KEYL3"
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   "outputs": [],
   "source": [
    "# Uncomment if notebook is run in Google Colab\n",
    "# %%capture\n",
    "# !pip install datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true,
    "id": "M1upfCmYEY5O"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\Anna\\miniconda3\\envs\\transformers\\Lib\\site-packages\\transformers\\utils\\generic.py:260: UserWarning: torch.utils._pytree._register_pytree_node is deprecated. Please use torch.utils._pytree.register_pytree_node instead.\n",
      "  torch.utils._pytree._register_pytree_node(\n"
     ]
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import re\n",
    "\n",
    "from evaluate import load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "hFbdPaloEb1l"
   },
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   "source": [
    "# Helper function\n",
    "def clean_string(string):\n",
    "    \"\"\"\n",
    "    Cleans the input string by removing asterisks, converting to lowercase,\n",
    "    and removing trailing whitespace characters.\n",
    "    \"\"\"\n",
    "    \n",
    "    string = re.sub('\\*', '', string).lower().rstrip()\n",
    "    return string"
   ]
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    "collapsed": true,
    "executionInfo": {
     "elapsed": 844678,
     "status": "ok",
     "timestamp": 1675026888326,
     "user": {
      "displayName": "Anna Kougioumtzidou",
      "userId": "08894778027574418607"
     },
     "user_tz": -120
    },
    "id": "RZxszX7TEb4T",
    "outputId": "99d15010-3cdd-48af-c32a-36ba39b436b5"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Found cached dataset reddit (C:/Users/Anna/.cache/huggingface/datasets/reddit/default/1.0.0/bd1bf9097540c9101f329c123d12c6c6a042f65e5f0ab7f9bbabb0a54d3c840e)\n",
      "Found cached dataset reddit_tifu (C:/Users/Anna/.cache/huggingface/datasets/reddit_tifu/long/1.1.0/3136b11fbef3f2517de1d720621af110bd29e6083aebeab0d8ec198c9f95dc95)\n"
     ]
    }
   ],
   "source": [
    "webis_tldr = load_dataset('reddit', split='train')\n",
    "reddit_tifu = load_dataset('reddit_tifu', 'long', split='train')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_tldr_df = webis_tldr.to_pandas()\n",
    "reddit_tifu_df = reddit_tifu.to_pandas()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### In the scope of our examination, for Webis-TLDR-17 we will keep only the data points that belong to the TIFU subreddit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_tldr_tifu_df = webis_tldr_df.loc[webis_tldr_df['subreddit'] == \"tifu\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52219"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(webis_tldr_tifu_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>body</th>\n",
       "      <th>normalizedBody</th>\n",
       "      <th>subreddit</th>\n",
       "      <th>subreddit_id</th>\n",
       "      <th>id</th>\n",
       "      <th>content</th>\n",
       "      <th>summary</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <td>Leterren</td>\n",
       "      <td>Harken all to my tale of dream pissing, for I ...</td>\n",
       "      <td>Harken all to my tale of dream pissing, for I ...</td>\n",
       "      <td>tifu</td>\n",
       "      <td>t5_2to41</td>\n",
       "      <td>c7f5mib</td>\n",
       "      <td>Harken all to my tale of dream pissing, for I ...</td>\n",
       "      <td>For those keeping count, I had a dream-within-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>530</th>\n",
       "      <td>TIFU_mod</td>\n",
       "      <td>[Link](\\n\\n**TIFU by combining magnets with my...</td>\n",
       "      <td>[Link]( \\n TIFU by combining magnets with my u...</td>\n",
       "      <td>tifu</td>\n",
       "      <td>t5_2to41</td>\n",
       "      <td>c7koxqi</td>\n",
       "      <td>Link]( \\n TIFU by combining magnets with my ur...</td>\n",
       "      <td>I'm not sure I'd advise sticking 74 magnets up...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>531</th>\n",
       "      <td>TIFU_mod</td>\n",
       "      <td>[Link](\\n\\n**TIFU by falling asleep while watc...</td>\n",
       "      <td>[Link]( \\n TIFU by falling asleep while watchi...</td>\n",
       "      <td>tifu</td>\n",
       "      <td>t5_2to41</td>\n",
       "      <td>c7koxw9</td>\n",
       "      <td>Link]( \\n TIFU by falling asleep while watchin...</td>\n",
       "      <td>I fell asleep after masturbating to porn and m...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>532</th>\n",
       "      <td>TIFU_mod</td>\n",
       "      <td>[Link](\\n\\n**TIFU. Dutch-ovened myself, puked....</td>\n",
       "      <td>[Link]( \\n TIFU. Dutch-ovened myself, puked. \\...</td>\n",
       "      <td>tifu</td>\n",
       "      <td>t5_2to41</td>\n",
       "      <td>c7koy14</td>\n",
       "      <td>Link]( \\n TIFU. Dutch-ovened myself, puked. \\n...</td>\n",
       "      <td>Dutch ovened myself, barfed. I'm also probably...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>533</th>\n",
       "      <td>TIFU_mod</td>\n",
       "      <td>[Link](\\n\\n**TIFU while peeing.**\\n\\nJust happ...</td>\n",
       "      <td>[Link]( \\n TIFU while peeing. \\n Just happened...</td>\n",
       "      <td>tifu</td>\n",
       "      <td>t5_2to41</td>\n",
       "      <td>c7koycb</td>\n",
       "      <td>Link]( \\n TIFU while peeing. \\n Just happened....</td>\n",
       "      <td>Thumb slipped, junk whipped, everything dripped.</td>\n",
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      "text/plain": [
       "       author                                               body  \\\n",
       "471  Leterren  Harken all to my tale of dream pissing, for I ...   \n",
       "530  TIFU_mod  [Link](\\n\\n**TIFU by combining magnets with my...   \n",
       "531  TIFU_mod  [Link](\\n\\n**TIFU by falling asleep while watc...   \n",
       "532  TIFU_mod  [Link](\\n\\n**TIFU. Dutch-ovened myself, puked....   \n",
       "533  TIFU_mod  [Link](\\n\\n**TIFU while peeing.**\\n\\nJust happ...   \n",
       "\n",
       "                                        normalizedBody subreddit subreddit_id  \\\n",
       "471  Harken all to my tale of dream pissing, for I ...      tifu     t5_2to41   \n",
       "530  [Link]( \\n TIFU by combining magnets with my u...      tifu     t5_2to41   \n",
       "531  [Link]( \\n TIFU by falling asleep while watchi...      tifu     t5_2to41   \n",
       "532  [Link]( \\n TIFU. Dutch-ovened myself, puked. \\...      tifu     t5_2to41   \n",
       "533  [Link]( \\n TIFU while peeing. \\n Just happened...      tifu     t5_2to41   \n",
       "\n",
       "          id                                            content  \\\n",
       "471  c7f5mib  Harken all to my tale of dream pissing, for I ...   \n",
       "530  c7koxqi  Link]( \\n TIFU by combining magnets with my ur...   \n",
       "531  c7koxw9  Link]( \\n TIFU by falling asleep while watchin...   \n",
       "532  c7koy14  Link]( \\n TIFU. Dutch-ovened myself, puked. \\n...   \n",
       "533  c7koycb  Link]( \\n TIFU while peeing. \\n Just happened....   \n",
       "\n",
       "                                               summary  \n",
       "471  For those keeping count, I had a dream-within-...  \n",
       "530  I'm not sure I'd advise sticking 74 magnets up...  \n",
       "531  I fell asleep after masturbating to porn and m...  \n",
       "532  Dutch ovened myself, barfed. I'm also probably...  \n",
       "533   Thumb slipped, junk whipped, everything dripped.  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "webis_tldr_tifu_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>ups</th>\n",
       "      <th>num_comments</th>\n",
       "      <th>upvote_ratio</th>\n",
       "      <th>score</th>\n",
       "      <th>documents</th>\n",
       "      <th>tldr</th>\n",
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       "      <td>115.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>0.88</td>\n",
       "      <td>115.0</td>\n",
       "      <td>this actually happened a couple of years ago. ...</td>\n",
       "      <td>confuse a 5th grade girl for a boy in front of...</td>\n",
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       "      <td>telling my dad that i love him.</td>\n",
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       "      <td>today i was going to have a bath after a long ...</td>\n",
       "      <td>peppermint + bath = burning cold ladybits.</td>\n",
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       "      <td>18.0</td>\n",
       "      <td>0.79</td>\n",
       "      <td>81.0</td>\n",
       "      <td>i haven't had a bath in practically years so, ...</td>\n",
       "      <td>got too high and too hot in the bath, almost c...</td>\n",
       "      <td>having a spliff in the bath.</td>\n",
       "    </tr>\n",
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      "text/plain": [
       "     ups  num_comments  upvote_ratio  score  \\\n",
       "0  115.0          23.0          0.88  115.0   \n",
       "1   16.0          12.0          0.79   16.0   \n",
       "2   55.0          10.0          0.85   55.0   \n",
       "3   90.0          20.0          0.92   90.0   \n",
       "4   81.0          18.0          0.79   81.0   \n",
       "\n",
       "                                           documents  \\\n",
       "0  this actually happened a couple of years ago. ...   \n",
       "1  it was last october, but i'm feeling the fall-...   \n",
       "2  so i had the brilliant idea to use veet hair r...   \n",
       "3  today i was going to have a bath after a long ...   \n",
       "4  i haven't had a bath in practically years so, ...   \n",
       "\n",
       "                                                tldr  \\\n",
       "0  confuse a 5th grade girl for a boy in front of...   \n",
       "1  i found my estranged dad, thought i loved him ...   \n",
       "2  had my balls burned by sauron and was left dev...   \n",
       "3         peppermint + bath = burning cold ladybits.   \n",
       "4  got too high and too hot in the bath, almost c...   \n",
       "\n",
       "                             title  \n",
       "0              gender-stereotyping  \n",
       "1  telling my dad that i love him.  \n",
       "2                i was deveeted...  \n",
       "3      wanting a pepperminty bath.  \n",
       "4     having a spliff in the bath.  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reddit_tifu_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the source texts only for both datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_source_texts = webis_tldr_tifu_df['content']\n",
    "tifu_source_texts = reddit_tifu_df['documents']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(webis_source_texts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_source_texts_df = pd.DataFrame({'index': webis_source_texts.index, 'text': webis_source_texts.values})\n",
    "tifu_source_texts_df = pd.DataFrame({'index': tifu_source_texts.index, 'text': tifu_source_texts.values})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_source_texts_df['text_uncased'] = webis_source_texts_df['text'].str.lower()\n",
    "tifu_source_texts_df['text_uncased'] = tifu_source_texts_df['text'].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_source_texts_df['text_clean'] = webis_source_texts_df['text_uncased'].apply(clean_string)\n",
    "tifu_source_texts_df['text_clean'] = tifu_source_texts_df['text_uncased'].apply(clean_string)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# webis_source_texts_list = webis_source_texts_df['text_clean'].tolist()\n",
    "# tifu_source_texts_list = tifu_source_texts_df['text_clean'].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>text</th>\n",
       "      <th>text_uncased</th>\n",
       "      <th>text_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>471</td>\n",
       "      <td>Harken all to my tale of dream pissing, for I ...</td>\n",
       "      <td>harken all to my tale of dream pissing, for i ...</td>\n",
       "      <td>harken all to my tale of dream pissing, for i ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>530</td>\n",
       "      <td>Link]( \\n TIFU by combining magnets with my ur...</td>\n",
       "      <td>link]( \\n tifu by combining magnets with my ur...</td>\n",
       "      <td>link]( \\n tifu by combining magnets with my ur...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>531</td>\n",
       "      <td>Link]( \\n TIFU by falling asleep while watchin...</td>\n",
       "      <td>link]( \\n tifu by falling asleep while watchin...</td>\n",
       "      <td>link]( \\n tifu by falling asleep while watchin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>532</td>\n",
       "      <td>Link]( \\n TIFU. Dutch-ovened myself, puked. \\n...</td>\n",
       "      <td>link]( \\n tifu. dutch-ovened myself, puked. \\n...</td>\n",
       "      <td>link]( \\n tifu. dutch-ovened myself, puked. \\n...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>533</td>\n",
       "      <td>Link]( \\n TIFU while peeing. \\n Just happened....</td>\n",
       "      <td>link]( \\n tifu while peeing. \\n just happened....</td>\n",
       "      <td>link]( \\n tifu while peeing. \\n just happened....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index                                               text  \\\n",
       "0    471  Harken all to my tale of dream pissing, for I ...   \n",
       "1    530  Link]( \\n TIFU by combining magnets with my ur...   \n",
       "2    531  Link]( \\n TIFU by falling asleep while watchin...   \n",
       "3    532  Link]( \\n TIFU. Dutch-ovened myself, puked. \\n...   \n",
       "4    533  Link]( \\n TIFU while peeing. \\n Just happened....   \n",
       "\n",
       "                                        text_uncased  \\\n",
       "0  harken all to my tale of dream pissing, for i ...   \n",
       "1  link]( \\n tifu by combining magnets with my ur...   \n",
       "2  link]( \\n tifu by falling asleep while watchin...   \n",
       "3  link]( \\n tifu. dutch-ovened myself, puked. \\n...   \n",
       "4  link]( \\n tifu while peeing. \\n just happened....   \n",
       "\n",
       "                                          text_clean  \n",
       "0  harken all to my tale of dream pissing, for i ...  \n",
       "1  link]( \\n tifu by combining magnets with my ur...  \n",
       "2  link]( \\n tifu by falling asleep while watchin...  \n",
       "3  link]( \\n tifu. dutch-ovened myself, puked. \\n...  \n",
       "4  link]( \\n tifu while peeing. \\n just happened....  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "webis_source_texts_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_source_texts_df.rename(columns={'index': 'webis_index'}, inplace=True)\n",
    "webis_source_texts_df.drop(columns=['text', 'text_uncased'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "    }\n",
       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>webis_index</th>\n",
       "      <th>text_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>471</td>\n",
       "      <td>harken all to my tale of dream pissing, for i ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>530</td>\n",
       "      <td>link]( \\n tifu by combining magnets with my ur...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>531</td>\n",
       "      <td>link]( \\n tifu by falling asleep while watchin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>532</td>\n",
       "      <td>link]( \\n tifu. dutch-ovened myself, puked. \\n...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>533</td>\n",
       "      <td>link]( \\n tifu while peeing. \\n just happened....</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   webis_index                                         text_clean\n",
       "0          471  harken all to my tale of dream pissing, for i ...\n",
       "1          530  link]( \\n tifu by combining magnets with my ur...\n",
       "2          531  link]( \\n tifu by falling asleep while watchin...\n",
       "3          532  link]( \\n tifu. dutch-ovened myself, puked. \\n...\n",
       "4          533  link]( \\n tifu while peeing. \\n just happened...."
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "webis_source_texts_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "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>index</th>\n",
       "      <th>text</th>\n",
       "      <th>text_uncased</th>\n",
       "      <th>text_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>this actually happened a couple of years ago. ...</td>\n",
       "      <td>this actually happened a couple of years ago. ...</td>\n",
       "      <td>this actually happened a couple of years ago. ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>it was last october, but i'm feeling the fall-...</td>\n",
       "      <td>it was last october, but i'm feeling the fall-...</td>\n",
       "      <td>it was last october, but i'm feeling the fall-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>so i had the brilliant idea to use veet hair r...</td>\n",
       "      <td>so i had the brilliant idea to use veet hair r...</td>\n",
       "      <td>so i had the brilliant idea to use veet hair r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>today i was going to have a bath after a long ...</td>\n",
       "      <td>today i was going to have a bath after a long ...</td>\n",
       "      <td>today i was going to have a bath after a long ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>i haven't had a bath in practically years so, ...</td>\n",
       "      <td>i haven't had a bath in practically years so, ...</td>\n",
       "      <td>i haven't had a bath in practically years so, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   index                                               text  \\\n",
       "0      0  this actually happened a couple of years ago. ...   \n",
       "1      1  it was last october, but i'm feeling the fall-...   \n",
       "2      2  so i had the brilliant idea to use veet hair r...   \n",
       "3      3  today i was going to have a bath after a long ...   \n",
       "4      4  i haven't had a bath in practically years so, ...   \n",
       "\n",
       "                                        text_uncased  \\\n",
       "0  this actually happened a couple of years ago. ...   \n",
       "1  it was last october, but i'm feeling the fall-...   \n",
       "2  so i had the brilliant idea to use veet hair r...   \n",
       "3  today i was going to have a bath after a long ...   \n",
       "4  i haven't had a bath in practically years so, ...   \n",
       "\n",
       "                                          text_clean  \n",
       "0  this actually happened a couple of years ago. ...  \n",
       "1  it was last october, but i'm feeling the fall-...  \n",
       "2  so i had the brilliant idea to use veet hair r...  \n",
       "3  today i was going to have a bath after a long ...  \n",
       "4  i haven't had a bath in practically years so, ...  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tifu_source_texts_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "tifu_source_texts_df.rename(columns={'index': 'tifu_index'}, inplace=True)\n",
    "tifu_source_texts_df.drop(columns=['text', 'text_uncased'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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>tifu_index</th>\n",
       "      <th>text_clean</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>this actually happened a couple of years ago. ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>it was last october, but i'm feeling the fall-...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>so i had the brilliant idea to use veet hair r...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>today i was going to have a bath after a long ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>i haven't had a bath in practically years so, ...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   tifu_index                                         text_clean\n",
       "0           0  this actually happened a couple of years ago. ...\n",
       "1           1  it was last october, but i'm feeling the fall-...\n",
       "2           2  so i had the brilliant idea to use veet hair r...\n",
       "3           3  today i was going to have a bath after a long ...\n",
       "4           4  i haven't had a bath in practically years so, ..."
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tifu_source_texts_df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding Reddit TIFU elements in Webis-TLDR-17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Broadcasting to compare elements element-wise\n",
    "comparison_matrix = webis_source_texts_df['text_clean'].values[:, None] == tifu_source_texts_df['text_clean'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "52219"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(webis_source_texts_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparison_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(52219, 42139)"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "comparison_matrix.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the values of the comparison matrix that are True\n",
    "matched_values = webis_source_texts_df['text_clean'][comparison_matrix.any(axis=1)].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5735"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(matched_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the coordinates (indices) of True values in the comparison matrix\n",
    "indices = np.where(comparison_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the coordinates to a list of tuples\n",
    "coordinates = list(zip(indices[0], indices[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5745"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(coordinates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(3881, 4093),\n",
       " (3890, 4083),\n",
       " (3891, 4082),\n",
       " (3894, 11560),\n",
       " (3899, 11557),\n",
       " (3906, 11551),\n",
       " (3909, 11548),\n",
       " (3914, 11543),\n",
       " (3933, 11528),\n",
       " (3939, 11523)]"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "coordinates[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding Webis-TLDR-17 elements in Reddit TIFU"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Broadcasting to compare elements element-wise\n",
    "comparison_matrix_2 = tifu_source_texts_df['text_clean'].values[:, None] == webis_source_texts_df['text_clean'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the values of the comparison matrix that are True\n",
    "matched_values_2 = tifu_source_texts_df['text_clean'][comparison_matrix_2.any(axis=1)].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5712"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(matched_values_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the coordinates (indices) of True values in the comparison matrix\n",
    "indices_2 = np.where(comparison_matrix_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the coordinates to a list of tuples\n",
    "coordinates_2 = list(zip(indices_2[0], indices_2[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5745"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(coordinates_2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checking the summaries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After the comparison for identical source texts (case-insensitive comparison) in Reddit-TIFU and Webis-TLDR-17 tifu subreddit,\n",
    "a similar comparison can be performed with regards to the summaries.\n",
    "\n",
    "Yet, identical summaries do not necessarily signify duplicate data points, for a number of reasons:\n",
    "- empty summaries, or summaries like \"Read title\" or \"Upvote\"\n",
    "- coincidental identical summaries (e.g. \"Think before you talk.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_summaries = webis_tldr_tifu_df['summary']\n",
    "tifu_summaries = reddit_tifu_df['tldr']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "webis_summaries_df = pd.DataFrame({'index': webis_summaries.index, 'text': webis_summaries.values})\n",
    "tifu_summaries_df = pd.DataFrame({'index': tifu_summaries.index, 'text': tifu_summaries.values})\n",
    "\n",
    "webis_summaries_df['text_uncased'] = webis_summaries_df['text'].str.lower()\n",
    "tifu_summaries_df['text_uncased'] = tifu_summaries_df['text'].str.lower()\n",
    "\n",
    "webis_summaries_df['text_clean'] = webis_summaries_df['text_uncased'].apply(clean_string)\n",
    "tifu_summaries_df['text_clean'] = tifu_summaries_df['text_uncased'].apply(clean_string)\n",
    "\n",
    "webis_summaries_list = webis_summaries_df['text_clean'].tolist()\n",
    "tifu_summaries_list = tifu_summaries_df['text_clean'].tolist()\n",
    "\n",
    "webis_summaries_df.rename(columns={'index': 'webis_index'}, inplace=True)\n",
    "webis_summaries_df.drop(columns=['text', 'text_uncased'], inplace=True)\n",
    "\n",
    "tifu_summaries_df.rename(columns={'index': 'tifu_index'}, inplace=True)\n",
    "tifu_summaries_df.drop(columns=['text', 'text_uncased'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Broadcasting to compare elements element-wise\n",
    "comparison_matrix = webis_summaries_df['text_clean'].values[:, None] == tifu_summaries_df['text_clean'].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the values of the comparison matrix that are True\n",
    "matched_values = webis_summaries_df['text_clean'][comparison_matrix.any(axis=1)].tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "24664"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(matched_values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Get the coordinates (indices) of True values in the comparison matrix\n",
    "indices = np.where(comparison_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert the coordinates to a list of tuples\n",
    "coordinates = list(zip(indices[0], indices[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
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