more_user_profiles.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "ff4ca471",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import requests as re\n",
    "import time\n",
    "import os\n",
    "import sqlite3\n",
    "import json\n",
    "import random\n",
    "# from mastodon import Mastodon\n",
    "import networkx as nx\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8c613c6f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# pandas options\n",
    "pd.set_option('display.max_columns', None)\n",
    "pd.options.mode.chained_assignment = None  # default='warn'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "id": "8d605105",
   "metadata": {},
   "outputs": [],
   "source": [
    "def select_relevant_following_fields(iterable, instance): \n",
    "    \"\"\"\n",
    "    Just a map to pull certain things out of the json\n",
    "    \n",
    "    \"\"\"\n",
    "    smaller_json = list(map(lambda x: \n",
    "                            dict(\n",
    "                                id=x[\"id\"],\n",
    "                                acct=x[\"acct\"],\n",
    "                                url=x[\"url\"], # so we can tell which server!\n",
    "                                created_at=x[\"created_at\"],\n",
    "                                followers_count=x[\"followers_count\"],\n",
    "                                following_count=x[\"following_count\"],\n",
    "                                statuses_count=x[\"statuses_count\"],\n",
    "                                last_status_at=x[\"last_status_at\"]\n",
    "                            ), \n",
    "                            iterable\n",
    "                           )\n",
    "                       )\n",
    "    \n",
    "    # add the server\n",
    "    new_list = []\n",
    "    for a_dict in smaller_json:\n",
    "        # add the server name\n",
    "        \n",
    "        # need both because there are different urls for local versus not\n",
    "        a_dict[\"instance\"] = a_dict[\"url\"].split(\"@\")[0].split(\"/users/\")[0]\n",
    "        \n",
    "        #check that the user instance is the one we need\n",
    "        if a_dict['instance'] == instance:\n",
    "            new_list.append(a_dict)\n",
    "   \n",
    "    return new_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "ba544e4d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def pull_profiles(file_path=\"data/profiles/\", local_only=True, offset=0, stride=80, write=True):\n",
    "    \"\"\"\n",
    "    \n",
    "    \"\"\"\n",
    "    profiles_df = pd.DataFrame()\n",
    "    chunk_df = pd.DataFrame()\n",
    "\n",
    "    req_stem = \"https://hci.social/api/v1/directory?limit=80&local={local_only}&order=new&offset={offset}\"\n",
    "    req_query = req_stem.format(offset=offset, local_only=\"true\" if local_only else \"false\")\n",
    "    r = re.get(req_query)\n",
    "\n",
    "    try:\n",
    "        profiles = r.json()\n",
    "    except Exception as e:\n",
    "        print(e, offset)\n",
    "\n",
    "    ii = 0\n",
    "\n",
    "    while len(profiles) > 0:\n",
    "        # keep going until you run out!\n",
    "\n",
    "        this_profiles_chunk = pd.DataFrame(select_relevant_fields(profiles))\n",
    "\n",
    "        # TODO: Don't concat these because we don't want huge CSVs! \n",
    "        # the newest thing is at the top, so concat old to the new\n",
    "        profiles_df = pd.concat([this_profiles_chunk, profiles_df], axis=0)\n",
    "\n",
    "        # Dataframe for 10 interations\n",
    "        chunk_df = pd.concat([this_profiles_chunk, chunk_df], axis=0)\n",
    "\n",
    "        # find out your new min_id\n",
    "        most_recent_created_time = this_profiles_chunk[\"created_at\"].max()\n",
    "\n",
    "        if (ii + 1) % 10 == 0:\n",
    "            print(\"caching results\") \n",
    "            if write:\n",
    "                chunk_df.to_csv(file_path + \"{}_profile_chunk_{}.csv\".format(\"local\" if local_only else \"global\", ii), index=False)\n",
    "            chunk_df = pd.DataFrame()\n",
    "\n",
    "        ii += 1\n",
    "        offset += stride\n",
    "\n",
    "        print(\"I am so proud of you, the last profile was created at {}\".format(most_recent_created_time))\n",
    "\n",
    "        # don't get booted off the API\n",
    "        time.sleep(1)\n",
    "\n",
    "        # make another call\n",
    "        req_query = req_stem.format(offset=offset, local_only=\"true\" if local_only else \"false\")\n",
    "        r = re.get(req_query)\n",
    "\n",
    "        try:\n",
    "            profiles = r.json()\n",
    "        except Exception as e:\n",
    "            print(e, offset)\n",
    "\n",
    "\n",
    "    print(\"DONE! You did so good!!\")\n",
    "            \n",
    "    if write:\n",
    "        profiles_df.to_csv(file_path + \"hci_social_profiles_{}.csv\".format(\"local\" if local_only else \"global\"), index=False)\n",
    "    \n",
    "    return profiles_df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "6601bf1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "# local_profiles = pull_profiles(local_only=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47ff12a9",
   "metadata": {},
   "source": [
    "## Trying shit out\n",
    "- Get all the followers and following for the user\n",
    "- Concat them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "12a75c16",
   "metadata": {},
   "outputs": [],
   "source": [
    "users_profiles = pd.read_csv(\"data/profiles/hci_social_profiles_local.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "bcd49f25",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\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>id</th>\n",
       "      <th>acct</th>\n",
       "      <th>url</th>\n",
       "      <th>created_at</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>statuses_count</th>\n",
       "      <th>last_status_at</th>\n",
       "      <th>instance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>108286624813793740</td>\n",
       "      <td>cqz</td>\n",
       "      <td>https://hci.social/@cqz</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>48</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "      <td>2023-11-03</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>108286142941695868</td>\n",
       "      <td>Gillian</td>\n",
       "      <td>https://hci.social/@Gillian</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>368</td>\n",
       "      <td>271</td>\n",
       "      <td>36</td>\n",
       "      <td>2022-12-23</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>108286014897638184</td>\n",
       "      <td>AndreaHCI</td>\n",
       "      <td>https://hci.social/@AndreaHCI</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-12-26</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>108285815791532398</td>\n",
       "      <td>izd</td>\n",
       "      <td>https://hci.social/@izd</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>39</td>\n",
       "      <td>22</td>\n",
       "      <td>37</td>\n",
       "      <td>2023-10-12</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>108285424167487793</td>\n",
       "      <td>shirinfeiz</td>\n",
       "      <td>https://hci.social/@shirinfeiz</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id        acct                             url  \\\n",
       "0  108286624813793740         cqz         https://hci.social/@cqz   \n",
       "1  108286142941695868     Gillian     https://hci.social/@Gillian   \n",
       "2  108286014897638184   AndreaHCI   https://hci.social/@AndreaHCI   \n",
       "3  108285815791532398         izd         https://hci.social/@izd   \n",
       "4  108285424167487793  shirinfeiz  https://hci.social/@shirinfeiz   \n",
       "\n",
       "                 created_at  followers_count  following_count  statuses_count  \\\n",
       "0  2022-05-12T00:00:00.000Z               48               20              24   \n",
       "1  2022-05-12T00:00:00.000Z              368              271              36   \n",
       "2  2022-05-11T00:00:00.000Z               13                9               1   \n",
       "3  2022-05-11T00:00:00.000Z               39               22              37   \n",
       "4  2022-05-11T00:00:00.000Z               12               20               0   \n",
       "\n",
       "  last_status_at             instance  \n",
       "0     2023-11-03  https://hci.social/  \n",
       "1     2022-12-23  https://hci.social/  \n",
       "2     2022-12-26  https://hci.social/  \n",
       "3     2023-10-12  https://hci.social/  \n",
       "4            NaN  https://hci.social/  "
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "users_profiles.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "18f39551",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_this_user_network_on_local_instance(user_id, instance, which=\"following\", verbose=False):\n",
    "    \"\"\"\n",
    "    Either get followers or following for a specific ID\n",
    "    \n",
    "    Params:\n",
    "        which (str):\n",
    "            one of followers or following\n",
    "        instance (str):\n",
    "            name of hci.social\n",
    "    \n",
    "    \n",
    "    \"\"\"\n",
    "\n",
    "    this_user_followers = []\n",
    "    this_batch_follower_list = []\n",
    "\n",
    "    followers_string = \"https://hci.social/api/v1/accounts/{id}/{which}?limit={limit}\"\n",
    "    next_query = followers_string.format(id=user_id, limit=80, which=which)\n",
    "    r = re.get(next_query)\n",
    "\n",
    "    if verbose:\n",
    "        print(next_query)\n",
    "\n",
    "    \n",
    "    # dumpster fire of a loop!\n",
    "    while True:\n",
    "        r = re.get(next_query)\n",
    "\n",
    "        try:\n",
    "            this_batch_follower_list = r.json()\n",
    "            # please don't break! but if it does, check here first!\n",
    "            next_query = str(r.headers[\"Link\"]).split('>; rel=\"next\",')[0].strip(\"<\")\n",
    "\n",
    "        except Exception as e:\n",
    "            print(e, id)\n",
    "            break\n",
    "\n",
    "        if len(this_batch_follower_list) == 0:\n",
    "            break\n",
    "\n",
    "        this_user_followers.extend(select_relevant_following_fields(this_batch_follower_list, instance))\n",
    "\n",
    "        if '; rel=\"prev\"' in next_query:\n",
    "            # I'm gonna puke\n",
    "            break\n",
    "\n",
    "        if verbose:\n",
    "            print(next_query)\n",
    "        \n",
    "    return this_user_followers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "69a171c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "25"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_user = get_this_user_network_on_local_instance(users_profiles.iloc[0][\"id\"], instance='https://hci.social/', which=\"followers\")\n",
    "\n",
    "len(test_user)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "c57cd587",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_users_df = users_profiles.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "72728fa9",
   "metadata": {},
   "outputs": [],
   "source": [
    "this_user_df = pd.DataFrame.from_records(test_user,\n",
    "                       columns=['id', 'acct', 'url', 'created_at','followers_count','following_count','statuses_count', 'last_status_at','instance'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "id": "b4baff18",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>acct</th>\n",
       "      <th>url</th>\n",
       "      <th>created_at</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>statuses_count</th>\n",
       "      <th>last_status_at</th>\n",
       "      <th>instance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>108286624813793740</td>\n",
       "      <td>cqz</td>\n",
       "      <td>https://hci.social/@cqz</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>48</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "      <td>2023-11-03</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>108286142941695868</td>\n",
       "      <td>Gillian</td>\n",
       "      <td>https://hci.social/@Gillian</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>368</td>\n",
       "      <td>271</td>\n",
       "      <td>36</td>\n",
       "      <td>2022-12-23</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>108286014897638184</td>\n",
       "      <td>AndreaHCI</td>\n",
       "      <td>https://hci.social/@AndreaHCI</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-12-26</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>108285815791532398</td>\n",
       "      <td>izd</td>\n",
       "      <td>https://hci.social/@izd</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>39</td>\n",
       "      <td>22</td>\n",
       "      <td>37</td>\n",
       "      <td>2023-10-12</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>108285424167487793</td>\n",
       "      <td>shirinfeiz</td>\n",
       "      <td>https://hci.social/@shirinfeiz</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>108236223653826827</td>\n",
       "      <td>axz</td>\n",
       "      <td>https://hci.social/@axz</td>\n",
       "      <td>2022-05-03T00:00:00.000Z</td>\n",
       "      <td>2421</td>\n",
       "      <td>1177</td>\n",
       "      <td>803</td>\n",
       "      <td>2023-11-19</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>108280547247259304</td>\n",
       "      <td>kjfeng</td>\n",
       "      <td>https://hci.social/@kjfeng</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>85</td>\n",
       "      <td>30</td>\n",
       "      <td>53</td>\n",
       "      <td>2023-10-19</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>108280517522446278</td>\n",
       "      <td>jbigham</td>\n",
       "      <td>https://hci.social/@jbigham</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>2895</td>\n",
       "      <td>1160</td>\n",
       "      <td>3850</td>\n",
       "      <td>2023-11-19</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>108236105999236686</td>\n",
       "      <td>msbernst</td>\n",
       "      <td>https://hci.social/@msbernst</td>\n",
       "      <td>2022-05-03T00:00:00.000Z</td>\n",
       "      <td>857</td>\n",
       "      <td>230</td>\n",
       "      <td>79</td>\n",
       "      <td>2023-10-23</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>108286710312907313</td>\n",
       "      <td>ruotongw</td>\n",
       "      <td>https://hci.social/@ruotongw</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>43</td>\n",
       "      <td>45</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-12-14</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>718 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    id        acct                             url  \\\n",
       "0   108286624813793740         cqz         https://hci.social/@cqz   \n",
       "1   108286142941695868     Gillian     https://hci.social/@Gillian   \n",
       "2   108286014897638184   AndreaHCI   https://hci.social/@AndreaHCI   \n",
       "3   108285815791532398         izd         https://hci.social/@izd   \n",
       "4   108285424167487793  shirinfeiz  https://hci.social/@shirinfeiz   \n",
       "..                 ...         ...                             ...   \n",
       "20  108236223653826827         axz         https://hci.social/@axz   \n",
       "21  108280547247259304      kjfeng      https://hci.social/@kjfeng   \n",
       "22  108280517522446278     jbigham     https://hci.social/@jbigham   \n",
       "23  108236105999236686    msbernst    https://hci.social/@msbernst   \n",
       "24  108286710312907313    ruotongw    https://hci.social/@ruotongw   \n",
       "\n",
       "                  created_at  followers_count  following_count  \\\n",
       "0   2022-05-12T00:00:00.000Z               48               20   \n",
       "1   2022-05-12T00:00:00.000Z              368              271   \n",
       "2   2022-05-11T00:00:00.000Z               13                9   \n",
       "3   2022-05-11T00:00:00.000Z               39               22   \n",
       "4   2022-05-11T00:00:00.000Z               12               20   \n",
       "..                       ...              ...              ...   \n",
       "20  2022-05-03T00:00:00.000Z             2421             1177   \n",
       "21  2022-05-11T00:00:00.000Z               85               30   \n",
       "22  2022-05-11T00:00:00.000Z             2895             1160   \n",
       "23  2022-05-03T00:00:00.000Z              857              230   \n",
       "24  2022-05-12T00:00:00.000Z               43               45   \n",
       "\n",
       "    statuses_count last_status_at             instance  \n",
       "0               24     2023-11-03  https://hci.social/  \n",
       "1               36     2022-12-23  https://hci.social/  \n",
       "2                1     2022-12-26  https://hci.social/  \n",
       "3               37     2023-10-12  https://hci.social/  \n",
       "4                0            NaN  https://hci.social/  \n",
       "..             ...            ...                  ...  \n",
       "20             803     2023-11-19  https://hci.social/  \n",
       "21              53     2023-10-19  https://hci.social/  \n",
       "22            3850     2023-11-19  https://hci.social/  \n",
       "23              79     2023-10-23  https://hci.social/  \n",
       "24               1     2022-12-14  https://hci.social/  \n",
       "\n",
       "[718 rows x 9 columns]"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.concat([all_users_df, this_user_df])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2dc5300",
   "metadata": {},
   "source": [
    "## Expanding the users dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "e21fd07c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_network_df(user_id):\n",
    "    users_followers = get_this_user_network_on_local_instance(user_id, instance='https://hci.social/', which=\"followers\")\n",
    "    users_followers = get_this_user_network_on_local_instance(user_id, instance='https://hci.social/', which=\"following\")\n",
    "    \n",
    "    users_followers_df = pd.DataFrame.from_records(users_followers,\n",
    "                       columns=['id', 'acct', 'url', 'created_at','followers_count','following_count','statuses_count', 'last_status_at','instance'])\n",
    "    \n",
    "    users_followeing_df = pd.DataFrame.from_records(users_followers,\n",
    "                       columns=['id', 'acct', 'url', 'created_at','followers_count','following_count','statuses_count', 'last_status_at','instance'])\n",
    "    \n",
    "    concated_network = pd.concat([users_followers_df, users_followeing_df]).drop_duplicates().reset_index(drop=True)\n",
    "    \n",
    "    print(\"compeleted network for user:\", user_id)\n",
    "    time.sleep(np.random.rand(1)[0] * 3)\n",
    "    \n",
    "    return concated_network"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "46412220",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for index, user in all_users_df.iterrows():\n",
    "    this_user_df = create_network_df(user['id'])\n",
    "    all_users_df = pd.concat([all_users_df, this_user_df])\n",
    "    all_users_df = all_users_df.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "e199022b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "22094"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_users_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "c3fc49ab",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_users_df_clean = all_users_df.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "c435beed",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_users_df_clean.reset_index(drop=True, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "1822c14a",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_users_df_clean.to_csv(\"data/profiles/extended_df.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "7d86e854",
   "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>id</th>\n",
       "      <th>acct</th>\n",
       "      <th>url</th>\n",
       "      <th>created_at</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>statuses_count</th>\n",
       "      <th>last_status_at</th>\n",
       "      <th>instance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1127</th>\n",
       "      <td>109245646986992073</td>\n",
       "      <td>Anas</td>\n",
       "      <td>https://hci.social/@Anas</td>\n",
       "      <td>2022-10-28T00:00:00.000Z</td>\n",
       "      <td>46</td>\n",
       "      <td>48</td>\n",
       "      <td>24</td>\n",
       "      <td>2023-11-11</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      id  acct                       url  \\\n",
       "1127  109245646986992073  Anas  https://hci.social/@Anas   \n",
       "\n",
       "                    created_at followers_count following_count statuses_count  \\\n",
       "1127  2022-10-28T00:00:00.000Z              46              48             24   \n",
       "\n",
       "     last_status_at             instance  \n",
       "1127     2023-11-11  https://hci.social/  "
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_users_df_clean[all_users_df_clean['acct'] == 'Anas']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47893942",
   "metadata": {},
   "source": [
    "## Running another interation of the code to extend the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "a6616ab8",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "compeleted network for user: 108286624813793740\n",
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      "compeleted network for user: 108286014897638184\n",
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      "'link' <built-in function id>\n",
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      "'link' <built-in function id>\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "'link' <built-in function id>\n",
      "compeleted network for user: 109253964349901029\n",
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      "compeleted network for user: 109419560855112485\n",
      "compeleted network for user: 109288725464881287\n",
      "'link' <built-in function id>\n",
      "'link' <built-in function id>\n",
      "compeleted network for user: 108285507233040442\n",
      "compeleted network for user: 109259282237632973\n",
      "compeleted network for user: 109543392532148413\n",
      "compeleted network for user: 109310369258734486\n"
     ]
    }
   ],
   "source": [
    "for index, user in all_users_df_clean.iterrows():\n",
    "    this_user_df = create_network_df(user['id'])\n",
    "    all_users_df = pd.concat([all_users_df, this_user_df])\n",
    "    all_users_df = all_users_df.drop_duplicates(subset=['id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "1ec713a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2165"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(all_users_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "623e8108",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_users_df_clean_extended = all_users_df.drop_duplicates(subset=['id'])\n",
    "all_users_df_clean_extended.reset_index(drop=True, inplace=True)\n",
    "all_users_df_clean_extended.to_csv(\"data/profiles/extended_df_complete.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "df83c935",
   "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>id</th>\n",
       "      <th>acct</th>\n",
       "      <th>url</th>\n",
       "      <th>created_at</th>\n",
       "      <th>followers_count</th>\n",
       "      <th>following_count</th>\n",
       "      <th>statuses_count</th>\n",
       "      <th>last_status_at</th>\n",
       "      <th>instance</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>108286624813793740</td>\n",
       "      <td>cqz</td>\n",
       "      <td>https://hci.social/@cqz</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>48</td>\n",
       "      <td>20</td>\n",
       "      <td>24</td>\n",
       "      <td>2023-11-03</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>108286142941695868</td>\n",
       "      <td>Gillian</td>\n",
       "      <td>https://hci.social/@Gillian</td>\n",
       "      <td>2022-05-12T00:00:00.000Z</td>\n",
       "      <td>368</td>\n",
       "      <td>271</td>\n",
       "      <td>36</td>\n",
       "      <td>2022-12-23</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>108286014897638184</td>\n",
       "      <td>AndreaHCI</td>\n",
       "      <td>https://hci.social/@AndreaHCI</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>13</td>\n",
       "      <td>9</td>\n",
       "      <td>1</td>\n",
       "      <td>2022-12-26</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>108285815791532398</td>\n",
       "      <td>izd</td>\n",
       "      <td>https://hci.social/@izd</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>39</td>\n",
       "      <td>22</td>\n",
       "      <td>37</td>\n",
       "      <td>2023-10-12</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>108285424167487793</td>\n",
       "      <td>shirinfeiz</td>\n",
       "      <td>https://hci.social/@shirinfeiz</td>\n",
       "      <td>2022-05-11T00:00:00.000Z</td>\n",
       "      <td>12</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>https://hci.social/</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   id        acct                             url  \\\n",
       "0  108286624813793740         cqz         https://hci.social/@cqz   \n",
       "1  108286142941695868     Gillian     https://hci.social/@Gillian   \n",
       "2  108286014897638184   AndreaHCI   https://hci.social/@AndreaHCI   \n",
       "3  108285815791532398         izd         https://hci.social/@izd   \n",
       "4  108285424167487793  shirinfeiz  https://hci.social/@shirinfeiz   \n",
       "\n",
       "                 created_at followers_count following_count statuses_count  \\\n",
       "0  2022-05-12T00:00:00.000Z              48              20             24   \n",
       "1  2022-05-12T00:00:00.000Z             368             271             36   \n",
       "2  2022-05-11T00:00:00.000Z              13               9              1   \n",
       "3  2022-05-11T00:00:00.000Z              39              22             37   \n",
       "4  2022-05-11T00:00:00.000Z              12              20              0   \n",
       "\n",
       "  last_status_at             instance  \n",
       "0     2023-11-03  https://hci.social/  \n",
       "1     2022-12-23  https://hci.social/  \n",
       "2     2022-12-26  https://hci.social/  \n",
       "3     2023-10-12  https://hci.social/  \n",
       "4            NaN  https://hci.social/  "
      ]
     },
     "execution_count": 153,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_users_df_clean_extended.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0e2faf14",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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