Social_Links_of_Interests.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "abcf3839",
   "metadata": {},
   "source": [
    "# Construct Social Links of Users\n",
    "\n",
    "by Nan BAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2182da1a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from argparse import Namespace\n",
    "from collections import Counter\n",
    "import pickle\n",
    "import os\n",
    "import urllib\n",
    "import flickrapi\n",
    "\n",
    "import json\n",
    "\n",
    "args = Namespace(\n",
    "    # Data and Path information\n",
    "    api_key = u'[api_key]',\n",
    "    api_secret = u'[api_secret]',\n",
    "    radius = 5,\n",
    "    save_dir = 'data_storage/',\n",
    "    tags = None,\n",
    "    len_grid = 1,\n",
    "    image_dir = 'data_storage/images/'\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "74ed9581",
   "metadata": {},
   "outputs": [],
   "source": [
    "size_df = pd.read_csv('Amsterdam/data_storage/metadata.csv',sep='\\t').rename(columns={'Unnamed: 0':'index'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "b48e51df",
   "metadata": {},
   "outputs": [],
   "source": [
    "size_df = pd.read_csv('Suzhou/data_storage/metadata.csv',sep='\\t').rename(columns={'Unnamed: 0':'index'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6bbb6562",
   "metadata": {},
   "outputs": [],
   "source": [
    "size_df = pd.read_csv('Venezia/data_storage/metadata.csv',sep='\\t').rename(columns={'Unnamed: 0':'index'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "e3d7f29d",
   "metadata": {},
   "outputs": [],
   "source": [
    "size_df = pd.read_csv('data_storage/images/metadata.csv',sep='\\t').rename(columns={'Unnamed: 0':'index'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "a7a85744",
   "metadata": {},
   "outputs": [],
   "source": [
    "owners = size_df['owner'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "2055fd1d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6077"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(owners)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "id": "22c96c01",
   "metadata": {},
   "outputs": [],
   "source": [
    "flickr = flickrapi.FlickrAPI(args.api_key, args.api_secret, format='json')\n",
    "contacts = {}\n",
    "groups = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "id": "098b498a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/95 collections finished\n",
      "'contact'\n",
      "11/95 collections finished\n",
      "'contact'\n",
      "'contact'\n",
      "21/95 collections finished\n",
      "'contact'\n",
      "31/95 collections finished\n",
      "'contact'\n",
      "41/95 collections finished\n",
      "'contact'\n",
      "'contact'\n",
      "51/95 collections finished\n",
      "61/95 collections finished\n",
      "'contact'\n",
      "'contact'\n",
      "'contact'\n",
      "'contact'\n",
      "71/95 collections finished\n",
      "'contact'\n",
      "81/95 collections finished\n"
     ]
    }
   ],
   "source": [
    "for owner in owners:\n",
    "    if not owner in contacts:\n",
    "        try:\n",
    "            contact_json = flickr.contacts.getPublicList(user_id=owner)\n",
    "            group_json = flickr.people.getPublicGroups(user_id=owner)\n",
    "\n",
    "            contacts[owner] = json.loads(contact_json.decode('utf-8'))['contacts']['contact']\n",
    "            groups[owner] = json.loads(group_json.decode('utf-8'))['groups']['group']\n",
    "        except Exception as e:\n",
    "            print(e)\n",
    "            continue\n",
    "    if len(contacts)%10==1:\n",
    "        print('{}/{} collections finished'.format(len(contacts),len(owners)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "id": "952dd129",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83"
      ]
     },
     "execution_count": 252,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(contacts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "id": "033a4acd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(groups)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "id": "47493f4a",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_pair = [(owner,contact['nsid']) for owner in contacts for contact in contacts[owner]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 255,
   "id": "78e4f182",
   "metadata": {},
   "outputs": [],
   "source": [
    "group_pair = [(owner,group['nsid'],group['name'],group['eighteenplus'],group['members'],group['pool_count']) for owner in groups for group in groups[owner]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 256,
   "id": "d0a015c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "70"
      ]
     },
     "execution_count": 256,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set([owner for owner in groups for group in groups[owner]]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 257,
   "id": "cee85f86",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "83"
      ]
     },
     "execution_count": 257,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set([owner for owner in groups]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 242,
   "id": "6f6c2aad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "17"
      ]
     },
     "execution_count": 242,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(set([owner for owner in groups]).difference(set([owner for owner in groups for group in groups[owner]])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 243,
   "id": "d90c2433",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 243,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "groups[list(set([owner for owner in groups]).difference(set([owner for owner in groups for group in groups[owner]])))[-1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "608c8537",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68971"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len([groups[owner] for owner in groups for group in groups[owner]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "ee236675",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "92158"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(contact_pair)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "0d5e0b87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "68971"
      ]
     },
     "execution_count": 192,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(group_pair)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "id": "c9766841",
   "metadata": {},
   "outputs": [
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       "                 0             1\n",
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     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "contact_df = pd.DataFrame(contact_pair)\n",
    "contact_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 245,
   "id": "5b8e4a07",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "191"
      ]
     },
     "execution_count": 245,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(contact_df[0].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "282cb89f",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df['inside'] = contact_df.apply(lambda x: x[1] in owners, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "89116d86",
   "metadata": {},
   "outputs": [
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       "              Source         Target  inside\n",
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       "\n",
       "[373 rows x 3 columns]"
      ]
     },
     "execution_count": 196,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "friendship = contact_df[contact_df['inside']].rename(columns={0:'Source',1:'Target'})\n",
    "friendship"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "4b4cbd92",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "135"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(friendship['Source'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "c7f59866",
   "metadata": {},
   "outputs": [
    {
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       "      <td>2769605@N21</td>\n",
       "      <td>! !^A Little Bit of Soap Level 3</td>\n",
       "      <td>0</td>\n",
       "      <td>994</td>\n",
       "      <td>11667</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583867</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>10758046@N00</td>\n",
       "      <td>~ PENTAX Cameras ~</td>\n",
       "      <td>0</td>\n",
       "      <td>8548</td>\n",
       "      <td>773628</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583868</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>64788317@N00</td>\n",
       "      <td>~*~Atmosphere~*~</td>\n",
       "      <td>0</td>\n",
       "      <td>11480</td>\n",
       "      <td>549670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583869</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>83292375@N00</td>\n",
       "      <td>α - Sony Alpha Cameras</td>\n",
       "      <td>0</td>\n",
       "      <td>24637</td>\n",
       "      <td>1245522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583870</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>1389174@N21</td>\n",
       "      <td>≈ monochrome ≈</td>\n",
       "      <td>0</td>\n",
       "      <td>21773</td>\n",
       "      <td>926884</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>583871</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>68841873@N00</td>\n",
       "      <td>☼Nature: Madre Tierra☼</td>\n",
       "      <td>0</td>\n",
       "      <td>4000</td>\n",
       "      <td>137869</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>583872 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               Source        Target  \\\n",
       "0       148125504@N04   3191023@N20   \n",
       "1       148125504@N04   1183996@N23   \n",
       "2       148125504@N04   1167706@N24   \n",
       "3       148125504@N04   2759861@N21   \n",
       "4       148125504@N04   2769605@N21   \n",
       "...               ...           ...   \n",
       "583867   48150664@N07  10758046@N00   \n",
       "583868   48150664@N07  64788317@N00   \n",
       "583869   48150664@N07  83292375@N00   \n",
       "583870   48150664@N07   1389174@N21   \n",
       "583871   48150664@N07  68841873@N00   \n",
       "\n",
       "                                            Group_Name  18+ Members  \\\n",
       "0       !           Fotografiando con Elena y Ricardo.    0    1404   \n",
       "1                     ! ! ! CÁNTABROS Y CANTABRIA¡ ¡ ¡    0    1369   \n",
       "2                     ! !^A Little Bit of Soap Level 1    0    2762   \n",
       "3                     ! !^A Little Bit of Soap Level 2    0    1307   \n",
       "4                     ! !^A Little Bit of Soap Level 3    0     994   \n",
       "...                                                ...  ...     ...   \n",
       "583867                              ~ PENTAX Cameras ~    0    8548   \n",
       "583868                                ~*~Atmosphere~*~    0   11480   \n",
       "583869                          α - Sony Alpha Cameras    0   24637   \n",
       "583870                                  ≈ monochrome ≈    0   21773   \n",
       "583871                          ☼Nature: Madre Tierra☼    0    4000   \n",
       "\n",
       "       Pool_Counts  \n",
       "0           194256  \n",
       "1            44966  \n",
       "2            90985  \n",
       "3            21229  \n",
       "4            11667  \n",
       "...            ...  \n",
       "583867      773628  \n",
       "583868      549670  \n",
       "583869     1245522  \n",
       "583870      926884  \n",
       "583871      137869  \n",
       "\n",
       "[583872 rows x 6 columns]"
      ]
     },
     "execution_count": 160,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interest = pd.DataFrame(group_pair).rename(columns={0:'Source',1:'Target',2:'Group_Name',3:'18+',4:'Members',5:'Pool_Counts'})\n",
    "interest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "23461032",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "293"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(interest['Source'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 246,
   "id": "e8031ffb",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df.to_csv('Amsterdam/data_storage/contacts.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "427da1c6",
   "metadata": {},
   "outputs": [],
   "source": [
    "friendship.to_csv('Amsterdam/data_storage/friendship.csv',sep='\\t')\n",
    "interest.to_csv('Amsterdam/data_storage/interest.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 259,
   "id": "e97faaf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df.to_csv('Suzhou/data_storage/contacts.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "ec66182c",
   "metadata": {},
   "outputs": [],
   "source": [
    "friendship.to_csv('Suzhou/data_storage/friendship.csv',sep='\\t')\n",
    "interest.to_csv('Suzhou/data_storage/interest.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "41928666",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df.to_csv('Venezia/data_storage/contacts.csv',sep='\\t')\n",
    "friendship.to_csv('Venezia/data_storage/friendship.csv',sep='\\t')\n",
    "interest.to_csv('Venezia/data_storage/interest.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "a0fc18cf",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df.to_csv('data_storage/images/contacts.csv',sep='\\t')\n",
    "friendship.to_csv('data_storage/images/friendship.csv',sep='\\t')\n",
    "interest.to_csv('data_storage/images/interest.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "bfb29faa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
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       "      <th>Target</th>\n",
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       "      <td>96099495@N05</td>\n",
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       "      <th>4</th>\n",
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       "      <th>...</th>\n",
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       "      <th>368</th>\n",
       "      <td>127547040@N07</td>\n",
       "      <td>53400673@N08</td>\n",
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       "    <tr>\n",
       "      <th>369</th>\n",
       "      <td>87413031@N03</td>\n",
       "      <td>33650137@N05</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>370</th>\n",
       "      <td>112273443@N02</td>\n",
       "      <td>145895983@N08</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>371</th>\n",
       "      <td>112273443@N02</td>\n",
       "      <td>123016824@N05</td>\n",
       "      <td>True</td>\n",
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       "    <tr>\n",
       "      <th>372</th>\n",
       "      <td>112273443@N02</td>\n",
       "      <td>141840400@N04</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>373 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Source         Target  inside\n",
       "0     47954272@N06   53400673@N08    True\n",
       "1     64148082@N02   88380809@N07    True\n",
       "2     64148082@N02   72647602@N04    True\n",
       "3     64148082@N02   96099495@N05    True\n",
       "4    186704588@N07   37472264@N04    True\n",
       "..             ...            ...     ...\n",
       "368  127547040@N07   53400673@N08    True\n",
       "369   87413031@N03   33650137@N05    True\n",
       "370  112273443@N02  145895983@N08    True\n",
       "371  112273443@N02  123016824@N05    True\n",
       "372  112273443@N02  141840400@N04    True\n",
       "\n",
       "[373 rows x 3 columns]"
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "friendship"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9ef979f8",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df = pd.read_csv('Venezia/data_storage/contacts.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "interest = pd.read_csv('Venezia/data_storage/interest.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "friendship = pd.read_csv('Venezia/data_storage/friendship.csv',sep='\\t').drop('Unnamed: 0',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "id": "02faefed",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df = pd.read_csv('Amsterdam/data_storage/contacts.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "interest = pd.read_csv('Amsterdam/data_storage/interest.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "friendship = pd.read_csv('Amsterdam/data_storage/friendship.csv',sep='\\t').drop('Unnamed: 0',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "727b7197",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df = pd.read_csv('Suzhou/data_storage/contacts.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "interest = pd.read_csv('Suzhou/data_storage/interest.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "friendship = pd.read_csv('Suzhou/data_storage/friendship.csv',sep='\\t').drop('Unnamed: 0',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "fdd51ed8",
   "metadata": {},
   "outputs": [],
   "source": [
    "contact_df = pd.read_csv('data_storage/images/contacts.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "interest = pd.read_csv('data_storage/images/interest.csv',sep='\\t').drop('Unnamed: 0',axis=1)\n",
    "friendship = pd.read_csv('data_storage/images/friendship.csv',sep='\\t').drop('Unnamed: 0',axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "d56b0734",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>894716</th>\n",
       "      <td>48150664@N07</td>\n",
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       "    </tr>\n",
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       "      <th>894717</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>64497386@N02</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>894718</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>121585339@N03</td>\n",
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       "    <tr>\n",
       "      <th>894719</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>101974306@N08</td>\n",
       "      <td>False</td>\n",
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       "    <tr>\n",
       "      <th>894720</th>\n",
       "      <td>48150664@N07</td>\n",
       "      <td>59230164@N07</td>\n",
       "      <td>False</td>\n",
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       "  </tbody>\n",
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       "<p>894721 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    0              1  inside\n",
       "0       148125504@N04   88562734@N00   False\n",
       "1       148125504@N04  140284390@N04   False\n",
       "2       148125504@N04   28132554@N00    True\n",
       "3       148125504@N04  155663969@N02   False\n",
       "4       148125504@N04  131256966@N08   False\n",
       "...               ...            ...     ...\n",
       "894716   48150664@N07   59649937@N05   False\n",
       "894717   48150664@N07   64497386@N02   False\n",
       "894718   48150664@N07  121585339@N03   False\n",
       "894719   48150664@N07  101974306@N08   False\n",
       "894720   48150664@N07   59230164@N07   False\n",
       "\n",
       "[894721 rows x 3 columns]"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "contact_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "c0b34941",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(117908, 117883)"
      ]
     },
     "execution_count": 135,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(interest['Target'].unique()),len(interest['Group_Name'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "72d4e97f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4883, 2454, 5627)"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(interest['Source'].unique()),len(friendship['Source'].unique()),len(contact_df['0'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "ceda372b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6077"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(owners)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "027c011b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "cd23f47f",
   "metadata": {},
   "outputs": [],
   "source": [
    "G1 = nx.from_pandas_edgelist(friendship, source='Source',target='Target')\n",
    "G2 = nx.from_pandas_edgelist(interest, source='Source',target='Target')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "4e4b6fa2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(8526, 809)"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(G1.edges()),len(G3.edges())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "29aa6315",
   "metadata": {},
   "outputs": [],
   "source": [
    "G3 = nx.bipartite.overlap_weighted_projected_graph(G2, interest['Source'].unique())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "151fe4d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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   ]
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  {
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   "execution_count": 122,
   "id": "4a39ad7a",
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   "outputs": [
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     "execution_count": 122,
     "metadata": {},
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    "nx.to_pandas_edgelist(G3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "02a804be",
   "metadata": {},
   "outputs": [
    {
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       "               Target  Group_Name  18+  Members  Pool_Counts\n",
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       "...               ...         ...  ...      ...          ...\n",
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     "execution_count": 178,
     "metadata": {},
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   ],
   "source": [
    "interest.groupby('Source').count()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "29375e25",
   "metadata": {},
   "outputs": [],
   "source": [
    "s = '64148082@N02'\n",
    "t = '72647602@N04'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3583bed8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.09836065573770492"
      ]
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     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "G3.edges[(s,t)]['weight']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "db955ee6",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_dict = {}\n",
    "for s in owners:\n",
    "    for t in owners:\n",
    "        social_dict[(s,t)] = {}\n",
    "        if s==t:\n",
    "            social_dict[(s,t)]['self'] = 1\n",
    "            social_dict[(s,t)]['friend'] = 1\n",
    "            social_dict[(s,t)]['interest'] = 1\n",
    "        else:\n",
    "            social_dict[(s,t)]['self'] = 0\n",
    "            social_dict[(s,t)]['friend'] = (s,t) in G1.edges()\n",
    "            if (s,t) in G3.edges():\n",
    "                social_dict[(s,t)]['interest'] = G3.edges[(s,t)]['weight']\n",
    "            else:\n",
    "                social_dict[(s,t)]['interest'] = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "c08dbd54",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df = pd.DataFrame(social_dict).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "61d78e32",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "social_df[social_df.interest>0].loc[social_df.interest<1]['interest'].hist(log=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "96d411fe",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  </tbody>\n",
       "</table>\n",
       "<p>35320 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            self friend  interest  mutual\n",
       "148125504@N04 30996501@N07     0  False  0.100789    True\n",
       "              103963823@N07    0  False  0.113518    True\n",
       "              131220333@N05    0  False  0.165109    True\n",
       "              38795342@N06     0  False  0.101571    True\n",
       "              130345501@N04    0   True  0.103535    True\n",
       "...                          ...    ...       ...     ...\n",
       "48150664@N07  134836250@N02    0   True  0.135729    True\n",
       "              121844793@N05    0  False  0.123953    True\n",
       "              116860703@N02    0  False  0.101227    True\n",
       "              130365893@N05    0  False  0.102041    True\n",
       "              127641458@N06    0  False  0.118987    True\n",
       "\n",
       "[35320 rows x 4 columns]"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "social_df[social_df.interest>0.1].loc[social_df.interest<1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "9f956c84",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df['mutual'] = social_df['interest'] > 0.1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "709e9e0d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">48150664@N07</th>\n",
       "      <th>46856873@N05</th>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.087719</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142199786@N05</th>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132571827@N06</th>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0.047859</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29127542@N04</th>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48150664@N07</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>36929929 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            self friend  interest  mutual\n",
       "148125504@N04 148125504@N04    1      1         1    True\n",
       "              32980384@N05     0  False  0.004769   False\n",
       "              96038677@N06     0  False         0   False\n",
       "              88380809@N07     0  False  0.012162   False\n",
       "              138486769@N02    0  False  0.033613   False\n",
       "...                          ...    ...       ...     ...\n",
       "48150664@N07  46856873@N05     0  False  0.087719   False\n",
       "              142199786@N05    0  False         0   False\n",
       "              132571827@N06    0  False  0.047859   False\n",
       "              29127542@N04     0  False         0   False\n",
       "              48150664@N07     1      1         1    True\n",
       "\n",
       "[36929929 rows x 4 columns]"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "social_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "562a2d84",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df.to_csv('Venezia/data_storage/social_links.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "id": "51b3752e",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df.to_csv('Amsterdam/data_storage/social_links.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "374e4763",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df.to_csv('Suzhou/data_storage/social_links.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "c2ea87dc",
   "metadata": {},
   "outputs": [],
   "source": [
    "social_df.to_csv('data_storage/images/social_links.csv',sep='\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9e48ef94",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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