effects_by_tweet_threshold.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "%matplotlib inline\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.patches as mpatches\n",
    "from numpy.random import RandomState\n",
    "from scipy import stats\n",
    "from permute.core import one_sample\n",
    "from utils import *\n",
    "\n",
    "prng = RandomState(42)\n",
    "sns.set_style('whitegrid')\n",
    "sns.set_context('paper', font_scale=1.5)\n",
    "\n",
    "FIG_FOLDER = 'figures/tweet_threshold_effects'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Calculate and plot robustness of effects to tweet threshold "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1730/1730 [00:04<00:00, 429.07it/s]\n"
     ]
    },
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>timeline</th>\n",
       "      <th>rank</th>\n",
       "      <th>prob_in_tl</th>\n",
       "      <th>user_id</th>\n",
       "      <th>user_summary_leaning</th>\n",
       "      <th>collected_at</th>\n",
       "      <th>shown_to_user</th>\n",
       "      <th>user_race</th>\n",
       "      <th>user_ethnicity</th>\n",
       "      <th>user_gender</th>\n",
       "      <th>...</th>\n",
       "      <th>full_text_len</th>\n",
       "      <th>tweet_age</th>\n",
       "      <th>partisanship</th>\n",
       "      <th>outgroup_animosity</th>\n",
       "      <th>outgroup_animosity_to_ingroup</th>\n",
       "      <th>outgroup_animosity_to_outgroup</th>\n",
       "      <th>ingroup_affect</th>\n",
       "      <th>outgroup_affect</th>\n",
       "      <th>user_time_key</th>\n",
       "      <th>user_summary_race</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Engagement</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>341</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-02-11 17:05:08.233</td>\n",
       "      <td>True</td>\n",
       "      <td>[White]</td>\n",
       "      <td>[None of these]</td>\n",
       "      <td>Man</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>1064.087217</td>\n",
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       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Stated Preference</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>341</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-02-11 17:05:08.233</td>\n",
       "      <td>True</td>\n",
       "      <td>[White]</td>\n",
       "      <td>[None of these]</td>\n",
       "      <td>Man</td>\n",
       "      <td>...</td>\n",
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       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Stated Preference with Downranking</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.625000</td>\n",
       "      <td>341</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-02-11 17:05:08.233</td>\n",
       "      <td>True</td>\n",
       "      <td>[White]</td>\n",
       "      <td>[None of these]</td>\n",
       "      <td>Man</td>\n",
       "      <td>...</td>\n",
       "      <td>23</td>\n",
       "      <td>1064.087217</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>341_2023-02-11 17:05:08.233</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Engagement</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>341</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-02-11 17:05:08.233</td>\n",
       "      <td>True</td>\n",
       "      <td>[White]</td>\n",
       "      <td>[None of these]</td>\n",
       "      <td>Man</td>\n",
       "      <td>...</td>\n",
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       "      <td>-1.0</td>\n",
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       "      <td>White</td>\n",
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       "      <th>4</th>\n",
       "      <td>Engagement</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>341</td>\n",
       "      <td>1</td>\n",
       "      <td>2023-02-11 17:05:08.233</td>\n",
       "      <td>True</td>\n",
       "      <td>[White]</td>\n",
       "      <td>[None of these]</td>\n",
       "      <td>Man</td>\n",
       "      <td>...</td>\n",
       "      <td>56</td>\n",
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       "      <td>White</td>\n",
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       "    <tr>\n",
       "      <th>93045</th>\n",
       "      <td>Stated Preference</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>165</td>\n",
       "      <td>-1</td>\n",
       "      <td>2023-02-28 05:55:47.757</td>\n",
       "      <td>True</td>\n",
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       "      <td>[None of these]</td>\n",
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       "      <td>165_2023-02-28 05:55:47.757</td>\n",
       "      <td>Asian or Native Hawaiian/other Pacific Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93046</th>\n",
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       "      <td>-1</td>\n",
       "      <td>2023-02-28 05:55:47.757</td>\n",
       "      <td>True</td>\n",
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       "      <td>Asian or Native Hawaiian/other Pacific Islander</td>\n",
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       "      <td>Asian or Native Hawaiian/other Pacific Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93048</th>\n",
       "      <td>Stated Preference</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>165</td>\n",
       "      <td>-1</td>\n",
       "      <td>2023-02-28 05:55:47.757</td>\n",
       "      <td>True</td>\n",
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       "      <td>Asian or Native Hawaiian/other Pacific Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "      <td>Stated Preference with Downranking</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.555556</td>\n",
       "      <td>165</td>\n",
       "      <td>-1</td>\n",
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       "      <td>True</td>\n",
       "      <td>[Asian]</td>\n",
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       "      <td>Man</td>\n",
       "      <td>...</td>\n",
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       "      <td>165_2023-02-28 05:55:47.757</td>\n",
       "      <td>Asian or Native Hawaiian/other Pacific Islander</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>93050 rows × 66 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 timeline  rank  prob_in_tl user_id  \\\n",
       "0                              Engagement   1.0    1.000000     341   \n",
       "1                       Stated Preference   NaN    0.625000     341   \n",
       "2      Stated Preference with Downranking   NaN    0.625000     341   \n",
       "3                              Engagement   2.0    1.000000     341   \n",
       "4                              Engagement   3.0    1.000000     341   \n",
       "...                                   ...   ...         ...     ...   \n",
       "93045                   Stated Preference   NaN    0.555556     165   \n",
       "93046  Stated Preference with Downranking   NaN    0.555556     165   \n",
       "93047                       Chronological  10.0    1.000000     165   \n",
       "93048                   Stated Preference   NaN    0.555556     165   \n",
       "93049  Stated Preference with Downranking   NaN    0.555556     165   \n",
       "\n",
       "       user_summary_leaning            collected_at  shown_to_user user_race  \\\n",
       "0                         1 2023-02-11 17:05:08.233           True   [White]   \n",
       "1                         1 2023-02-11 17:05:08.233           True   [White]   \n",
       "2                         1 2023-02-11 17:05:08.233           True   [White]   \n",
       "3                         1 2023-02-11 17:05:08.233           True   [White]   \n",
       "4                         1 2023-02-11 17:05:08.233           True   [White]   \n",
       "...                     ...                     ...            ...       ...   \n",
       "93045                    -1 2023-02-28 05:55:47.757           True   [Asian]   \n",
       "93046                    -1 2023-02-28 05:55:47.757           True   [Asian]   \n",
       "93047                    -1 2023-02-28 05:55:47.757           True   [Asian]   \n",
       "93048                    -1 2023-02-28 05:55:47.757           True   [Asian]   \n",
       "93049                    -1 2023-02-28 05:55:47.757           True   [Asian]   \n",
       "\n",
       "        user_ethnicity user_gender  ... full_text_len    tweet_age  \\\n",
       "0      [None of these]         Man  ...            23  1064.087217   \n",
       "1      [None of these]         Man  ...            23  1064.087217   \n",
       "2      [None of these]         Man  ...            23  1064.087217   \n",
       "3      [None of these]         Man  ...           136   501.270550   \n",
       "4      [None of these]         Man  ...            56  1195.270550   \n",
       "...                ...         ...  ...           ...          ...   \n",
       "93045  [None of these]         Man  ...           217   355.095950   \n",
       "93046  [None of these]         Man  ...           217   355.095950   \n",
       "93047  [None of these]         Man  ...            86   201.162617   \n",
       "93048  [None of these]         Man  ...            86   201.162617   \n",
       "93049  [None of these]         Man  ...            86   201.162617   \n",
       "\n",
       "      partisanship outgroup_animosity outgroup_animosity_to_ingroup  \\\n",
       "0              0.0                  0                             0   \n",
       "1              0.0                  0                             0   \n",
       "2              0.0                  0                             0   \n",
       "3              1.0                  1                             0   \n",
       "4              0.0                  0                             0   \n",
       "...            ...                ...                           ...   \n",
       "93045          0.0                  0                             0   \n",
       "93046          0.0                  0                             0   \n",
       "93047          0.0                  0                             0   \n",
       "93048          0.0                  0                             0   \n",
       "93049          0.0                  0                             0   \n",
       "\n",
       "      outgroup_animosity_to_outgroup ingroup_affect outgroup_affect  \\\n",
       "0                                  0            0.0             0.0   \n",
       "1                                  0            0.0             0.0   \n",
       "2                                  0            0.0             0.0   \n",
       "3                                  1           -1.0            -1.0   \n",
       "4                                  0            0.0             0.0   \n",
       "...                              ...            ...             ...   \n",
       "93045                              0            0.0             0.0   \n",
       "93046                              0            0.0             0.0   \n",
       "93047                              0            0.0             0.0   \n",
       "93048                              0            0.0             0.0   \n",
       "93049                              0            0.0             0.0   \n",
       "\n",
       "                     user_time_key  \\\n",
       "0      341_2023-02-11 17:05:08.233   \n",
       "1      341_2023-02-11 17:05:08.233   \n",
       "2      341_2023-02-11 17:05:08.233   \n",
       "3      341_2023-02-11 17:05:08.233   \n",
       "4      341_2023-02-11 17:05:08.233   \n",
       "...                            ...   \n",
       "93045  165_2023-02-28 05:55:47.757   \n",
       "93046  165_2023-02-28 05:55:47.757   \n",
       "93047  165_2023-02-28 05:55:47.757   \n",
       "93048  165_2023-02-28 05:55:47.757   \n",
       "93049  165_2023-02-28 05:55:47.757   \n",
       "\n",
       "                                     user_summary_race  \n",
       "0                                                White  \n",
       "1                                                White  \n",
       "2                                                White  \n",
       "3                                                White  \n",
       "4                                                White  \n",
       "...                                                ...  \n",
       "93045  Asian or Native Hawaiian/other Pacific Islander  \n",
       "93046  Asian or Native Hawaiian/other Pacific Islander  \n",
       "93047  Asian or Native Hawaiian/other Pacific Islander  \n",
       "93048  Asian or Native Hawaiian/other Pacific Islander  \n",
       "93049  Asian or Native Hawaiian/other Pacific Islander  \n",
       "\n",
       "[93050 rows x 66 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Load data\n",
    "df = load_to_df('data/twitter_data.json')\n",
    "df = df[df['shown_to_user']==True].reset_index(drop=True)\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:794: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  group_counts = pol_df.groupby([\"user_time_key\", \"timeline\"]).size().unstack(fill_value=0)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:426: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby([\"user_time_key\", \"timeline\"])[keys].agg(**aggregations)\n",
      "/Users/micah/Developer/Research Code/twitter-analysis/utils.py:437: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  return grouped.groupby([\"user_id\", \"timeline\"]).mean()\n"
     ]
    }
   ],
   "source": [
    "# Calculate effects for engagement timeline\n",
    "eng_effects_5 = get_effects(df, Timeline.ENGAGEMENT, 5)\n",
    "eng_effects_6 = get_effects(df, Timeline.ENGAGEMENT, 6)\n",
    "eng_effects_7 = get_effects(df, Timeline.ENGAGEMENT, 7)\n",
    "eng_effects_8 = get_effects(df, Timeline.ENGAGEMENT, 8)\n",
    "eng_effects_9 = get_effects(df, Timeline.ENGAGEMENT, 9)\n",
    "eng_effects_10 = get_effects(df, Timeline.ENGAGEMENT, 10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Add in rank column\n",
    "eng_effects_5['Rank'] = 5\n",
    "eng_effects_6['Rank'] = 6\n",
    "eng_effects_7['Rank'] = 7\n",
    "eng_effects_8['Rank'] = 8\n",
    "eng_effects_9['Rank'] = 9\n",
    "eng_effects_10['Rank'] = 10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create groupings for individual graphs.\n",
    "reader_prefs = [\"Reader pref (political)\", \"Reader pref (overall)\"]\n",
    "animosity = ['Out-group animosity']\n",
    "partisanship = ['Partisanship']\n",
    "\n",
    "\n",
    "outgroup_perception = [ 'Out-group perception (right users)',  'Out-group perception (left users)',  'Out-group perception']\n",
    "ingroup_perception = [ 'In-group perception (right users)',  'In-group perception (left users)', 'In-group perception']\n",
    "\n",
    "reader_political = ['Reader happy (political)', 'Reader anxious (political)', 'Reader sad (political)', 'Reader angry (political)']\n",
    "author_political =  ['Author happy (political)', 'Author anxious (political)', 'Author sad (political)', 'Author angry (political)']\n",
    "reader_overall = ['Reader happy (overall)', 'Reader anxious (overall)', 'Reader sad (overall)', 'Reader angry (overall)']\n",
    "author_overall = [ 'Author happy (overall)', 'Author anxious (overall)', 'Author sad (overall)', 'Author angry (overall)']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "eng_effects_combined = pd.concat([eng_effects_5, eng_effects_6, eng_effects_7, eng_effects_8, eng_effects_9, eng_effects_10])\n",
    "eng_effects_combined['Outcome'] = eng_effects_combined['Outcome'].apply(lambda x: x[0] + x[1:].lower())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "eng_effects_combined = eng_effects_combined.set_index('Outcome')\n",
    "rank = eng_effects_combined['Rank'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.rcParams[\"mathtext.fontset\"] = \"cm\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 700x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "general_group = reader_prefs\n",
    "fig, ax = plt.subplots(figsize=(7, 5))\n",
    "\n",
    "\n",
    "lplot = sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=ax, marker=\"o\", markersize=8)\n",
    "lplot.axhline(0,color='black', linewidth=2)\n",
    "ax.margins(x=0)\n",
    "plt.legend()\n",
    "ax.set_title(\"Reader preferences\", fontweight=\"bold\")\n",
    "ax.set_xlabel(r'$k$')\n",
    "ax.set_ylabel(r\"Average treatment effect with top $k$ tweets\")\n",
    "ax.fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "ax.fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "ax.set_yticks(np.arange(-.1, .11, .05))\n",
    "ax.grid(False)\n",
    "plt.savefig(f\"{FIG_FOLDER}/reader_prefs.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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j9dNPP+VZ27Ywvu9dzZo1rce+92eoU6eO9dh7/M2bN1vnlNdee60VhEruCQ/x8fH65JNPdO7cOW3fvl1t27ZVq1attHXrVn300Uf65JNP1KpVK11xxRW66qqr1LFjR1s3fWvZsqUuvfRS/fjjj/rqq6/09NNP69ChQ9q6dask9zktN5UDyg4CWAD4HQwbNkxdunSRYRiKiIhQjRo11LBhQ79ZF5mZmZowYYI+/PBD6+Subt26aty4sbZv3y5JAS+ltxu+Su4T4UmTJukf//iHtm7dqpMnT2rx4sVavHixxo8frz59+mjChAnWLzRff/21XnzxRWvGQVRUlC6//HLrxD+/S/59f7nIL0gdP3686tSpo3nz5iklJUXbt2/X9u3bNWPGDNWqVUt///vf/W4I4VWtWjW/5961tyTluSFCQXIfx3fmbGG/xAEAgNJXpUoVRUdH6/Tp0zp9+rQOHz6smJiYgG19w8LcVxlJec9psrOzi1XLjBkz9PHHH/tt69Spk98M19xX6TidTlWrVk3Hjh3L97i5z/98l0nyDQ+9fF9/oCWVivs6q1at6ve8OOdLe/fu1dixY63lrcLCwtSsWTPVrFlTx48fz7efb+Ap5X8uWRjfoN03oPQ9vnc5BCnnvfF93wJ9PfluO3XqlCTp3Xff1YQJE/T5558rPT3dWud20qRJiouL0yuvvKK2bdue1+uQpAEDBugf//iHjhw5og0bNljhqyTryjgAZQNrwALA76BFixZKSEhQfHy8unfvrpYtW/qFr5KUmJioGTNmKC0tTffee6+WLVumpUuXWpfp56dChQpBqbFr16766KOPtHjxYj3//PMaOHCgatWqJdM09cUXX1iX9//000966KGHdODAAbVv314ffPCB1q1bp/fee6/QMYryKXxUVJTGjh2r1atXa/LkyRo1apQ6dOggwzB07NgxPfLII343C/MyDKP4LzqAw4cP+z33Hcs3QAYAAGWTYRjq0KGD9Ty/NUVdLpffuvWdOnWy+nvlnoXqO2PWDt91aXOf12RlZRW67rx37VIv35mcgS7h9z2/8Yalvq/Td9ZpdnZ2oVcP5R6jqOdLWVlZ+vOf/6wNGzaodu3aSkxM1Lp16/TRRx9Z9z3IT7Bmc+Z3HN8P7wPxfY9zny/m3uYNyGvUqKEJEyZo1apVSkxM1J133qlWrVpJkn777Tc98MADxQ71ffXv398Ki7/88kt99dVXktzLWLRp0+a8jwsg+AhgAaCM8J4weW9I4F2ba8eOHQX28/2EPtC2otyA6sMPP9RTTz2lO++8U3Xq1NHgwYM1YcIEv19YvDcIW7ZsmXWSfsstt+jyyy+X0+m0Zuna8fPPP+vVV1/Vvffeq//973/q1q2bRo8erZkzZ2rIkCGS3DfW2Llzp+2x8vPpp5/6vWeLFy+2Hjdr1qzExgUAAMHj+wF2YmJiwPOUiRMnWssVXXzxxbr66qsl+S9hkDtozO98xxtm5j7vGj9+vHbt2uX3Z8aMGYqNjbXG+e677/zWn12wYEGByw9Iec//6tWrp9q1a0uSVq5c6Xfj1vT0dOuczul0Wpfg5/c6d+zYUejVQ4sWLVJGRob1vKjnS7t27dK+ffskudfdv+aaaxQZGanU1FT9/PPPBY5Z2lq0aKHw8HBJ0ueff+73b3bs2DF9/fXXktwBdPPmzfXDDz9owoQJuvvuu7V27Vpdc801evzxx/XRRx9ZX2tHjx4NeJNdX75Bee6vr5iYGGtphgULFmj9+vWSuPkWUBaxBAEAlBHey6GysrL0f//3f4qPj9eaNWusxf4l+Z3oFsR3VsS2bds0f/58xcTEqGvXrgHb79q1S3PnzpUk3XXXXbrpppvkcDisUFjKuSzP97KtN998U6Zp6tSpU5o8eXKx68ytcuXKmjJlijIzM7Vq1SodPnxYjRo1UlJSknWjCsn9S0ZJ2bhxo0aNGqU//OEP2rJliz766CNJ7pPp+Pj4EhsXAAAET/fu3XXdddfps88+U0pKioYMGaJBgwapbdu2Sk1N1eeff66VK1dKcoeZL7zwgjUzslq1atYSBjt37tSkSZPUqVMnvf/++/mub+oNM1NSUjRz5kxVrlxZAwYMyLe+iIgI9e/fX++//77OnDmj22+/XUOHDtXBgwf17rvvFvv1Op1ODRkyRK+//royMjI0dOhQjRw5UpGRkZozZ461bNRNN91kLVHgu8b/5MmT1bRpU2VkZGjChAmFjnfgwAENHz5ct9xyi3777TfrSqiwsLACwz/f88jPP/9cl156qapWrapZs2ZZs2jP9zyypFWtWlU33HCD5s2bp+PHj2vw4MEaNmyYdQM07+zokSNHKjw8XA6Hwzo/3rp1q0aOHKm6devqp59+su7xUKFCBb/Z0IH4BuUzZsxQzZo1rZvaSu5lCFasWOG3ZAUBLFD2EMACQBnxxz/+0VoLa+HChVq4cKEkKTw83Jpx6l1jtTA1atTQRRddpIMHD+rw4cN6/PHHNWjQoHwD2AceeEDff/+9du/erTVr1mjNmjV++6tVq6YHHnhAknTNNdeoevXqOnHihPbv368nn3zSauettah15la7dm397W9/09NPP63U1FRr2QNfw4cP97uBV7A1a9ZM33zzjb755htrm2EYevbZZ0vk5hwAAKBkjBs3TpL02WefKT09XTNmzLDuGu8VGRmp8ePH+50jORwO3Xjjjdbd51955RVJ7vOBa665RkuWLMkzVvPmzfXjjz/KNE09//zzatCgQYEBrCTdd999+vrrr3Xs2DFt27ZNTz31lCT3ucj+/ft19uzZYi2xNGrUKG3btk1LlizR4cOH9dJLL/ntv+KKK/zO27p166bY2FgdOnRIhw8f1ogRIyS5P+hu1qxZgVccNW3a1FrP1NdDDz3kdwOw3OLi4tSxY0etXbtWaWlpevnll6193vPIEydOKD09PWjLbAXTU089pb1792rz5s3au3evnn32Wb/9ffv21T333CPJfZOsUaNG6e2331ZycrL1deTrkUceUaVKlQocs3nz5tZ56euvv66IiAgNGTLE+tro3bu3KlWqZAXAbdq0KdFzZQDnhyUIAKCMuPnmm/XCCy/o0ksvVcWKFVWvXj3169dPH330kXVitnTp0iIfb/z48brssssUHh6u2rVrFzhrtFq1apo1a5YefvhhNWvWTFWqVFF4eLguvvhiDRo0SB9//LF1IlezZk1NmzZN3bt3V9WqVVWtWjW1a9dO//jHP3TTTTdJct8lNtA6rUUxaNAgzZw5U/Hx8apbt67Cw8NVpUoVdejQQRMmTPD7xaEk/OUvf9ETTzyhevXqKSIiQq1atdLbb7+t66+/vkTHBQAAwVWhQgX985//1OTJk3XttdfqoosuUnh4uCpVqqSmTZvqrrvu0hdffKF+/frl6ft///d/+vOf/6w6deqoYsWKuuKKKzR58uSAbSVp9OjR6tatmypUqKDo6Gg1bty40PpiY2M1Z84cJSQkqHLlyoqOjtaNN96oqVOnWuuR+s5+LExYWJgSExP18ssvq3PnzqpataoqVqyoZs2aacyYMZo6darfPQiioqI0depUXX311YqKilL16tX1xz/+UR9++GGhN3m96aab9Morr6hhw4YKDw/XpZdeqvHjx1vhY34Mw9DEiRN1yy23KCYmRlFRUbrsssv0wAMP6O9//7sk99Vgy5cvL/Lr/j1VrlxZs2bN0t/+9jddfvnlqly5sqKiotS2bVu9+OKL+ve//+23xuzo0aP11ltvqVu3boqJiVFYWJiqVaumq666SomJiVboXZA777xTffv2VVRUlKKiotS6dWulp6db+yMjI9WrVy/rObNfgbLJMIuyOCAAAOXY66+/rjfeeEOSe1mFhISEUq4IAACUd//73/9UqVIl1alTR5dddpm1hFRqaqo6duyozMxMde3aVVOnTi3dQj3mzZunJ554QpL0xBNPFCk8RMnLysrSddddp19++UVOp1PffvttocsaAPj9lbslCJKSkvTKK69o1apVyszMVJcuXTRmzJgCL4OQpLS0NL3xxhv67LPPlJycrGbNmunhhx/Oc7luamqq/vWvf+nzzz9XcnKy6tWrp1tvvVXDhw8vyZcFAAAAAChHpk2bpm3btkmS4uPjdf311ys9PV3z58+3lp/y3jALyG358uXKyMjQJ598ol9++UWSdPXVVxO+AmVUuQpgT548qeHDh+vs2bO6/fbbFRERocmTJ+vWW2/V/PnzVaNGjXz7Pvroo1q6dKmGDh2qRo0aae7cubrrrrs0bdo0dejQwWr3wAMPaMWKFRo4cKDatm2rpUuX6sUXX1RycrIefvjh3+FVAgAAAABC3R133KG//vWvkqSvv/5aX3/9td/+2rVra+jQoaVRGkLAlClTrBvJSe4bu3nv2QCg7ClXAezUqVO1f/9+zZ07V61atZLkvvvlwIED9e677+rxxx8P2G/VqlVavHix32UUAwcOVP/+/fXSSy9p3rx5kqQtW7ZoxYoVGjx4sJ5//nlJ0p/+9CcNHz5ckyZN0h133KGqVauW/AsFAAAAAIS0G264QdHR0frvf/+r7du36+TJk3I4HIqNjVW3bt107733qmbNmqVdJsqo5s2ba9OmTXI4HGrevLkeeOABKwcBUPaUqzVgExISVKtWLc2ZM8dv+5133qkff/wx34W8n3zySX3yySdas2aN36Lkb7/9tl577TV98cUXatCggRYsWKBHH31UEydOVN++fa12kyZN0iuvvKL3339fbdu2LZHXBgAAAAAAACD0OEq7gGA5deqU9u3bF/ATn5YtW+rIkSM6cuRIwL5bt25Vw4YN/cJXbz/vfklq0KCBJOmnn37ya/fbb79JkurUqWPrNQAAAAAAAAAoX8rNEgSHDx+WJMXExOTZ5w1GDx48GDAkPXz4sNq0aZNvv6SkJElSq1atdMstt2jSpEmKi4tT27ZttWLFCs2bN0/9+/dX3bp1g/Z6AAAAAAAAAIS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",
      "text/plain": [
       "<Figure size 1400x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "fix, axes = plt.subplots(2, 2, figsize=(14, 10), sharey='row')\n",
    "axes = np.append(axes[0], axes[1])\n",
    "\n",
    "general_group = animosity\n",
    "lplot = sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[1], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[1].legend(loc='lower left')\n",
    "axes[1].set_title(\"Out-group animosity\", fontweight=\"bold\")\n",
    "axes[1].set_xlabel(r\"$k$\")\n",
    "axes[1].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "general_group = partisanship\n",
    "\n",
    "lplot = sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[0], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[0].legend(loc='lower left')\n",
    "axes[0].set_title(\"Partisanship\",  fontweight=\"bold\")\n",
    "axes[0].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[0].set_xlabel(r\"$k$\")\n",
    "axes[0].set_ylabel(r'Average treatment effect with top $k$ tweets')\n",
    "axes[0].set_yticks(np.arange(-.08, .081, .04))\n",
    "\n",
    "general_group = ingroup_perception\n",
    "\n",
    "lplot= sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[2], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0,color='black', linewidth=2)\n",
    "\n",
    "axes[2].legend(loc='lower left')\n",
    "axes[2].set_title(\"In-group perception\",  fontweight=\"bold\")\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].set_xlabel(r\"$k$\")\n",
    "axes[2].set_ylabel(r\"Average treatment effect with top $k$ tweets\")\n",
    "general_group = outgroup_perception\n",
    "\n",
    "lplot= sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[3], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[3].legend(loc='upper left')\n",
    "axes[3].set_title(\"Out-group perception\",  fontweight=\"bold\")\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].set_ylabel(None)\n",
    "axes[3].set_xlabel(r\"$k$\")\n",
    "axes[3].set_yticks(np.arange(-.1, .11, .05))\n",
    "\n",
    "axes[0].margins(x=0)\n",
    "axes[1].margins(x=0)\n",
    "axes[2].margins(x=0)\n",
    "axes[3].margins(x=0)\n",
    "\n",
    "# sns.despine()\n",
    "axes[0].grid(False)\n",
    "axes[1].grid(False)\n",
    "axes[2].grid(False)\n",
    "axes[3].grid(False)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f\"{FIG_FOLDER}/political_effects.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Emotion graphs\n",
    "fix, axes = plt.subplots(2, 2, figsize=(14, 10), sharey='row')\n",
    "axes = np.append(axes[0], axes[1])\n",
    "\n",
    "general_group = reader_political\n",
    "lplot = sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[3], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[3].legend(loc='lower left')\n",
    "axes[3].set_title(\"Reader emotions (political)\", fontweight=\"bold\")\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], color=list(sns.color_palette())[3], alpha=0.2, label='Confidence Interval')\n",
    "axes[3].set_xlabel(r\"$k$\")\n",
    "general_group = author_political\n",
    "\n",
    "lplot = sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[2], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[2].legend(loc='lower left')\n",
    "axes[2].set_title(\"Author emotions (political)\",  fontweight=\"bold\")\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], color=list(sns.color_palette())[3], alpha=0.2, label='Confidence Interval')\n",
    "axes[2].set_xlabel(r\"$k$\")\n",
    "axes[2].set_ylabel(r\"Average treatment effect with top $k$ tweets\")\n",
    "axes[2].set_yticks(np.arange(-.5, .51, .25))\n",
    "\n",
    "general_group = reader_overall\n",
    "\n",
    "lplot= sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[1], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0,color='black', linewidth=2)\n",
    "\n",
    "axes[1].legend(loc='lower left')\n",
    "axes[1].set_title(\"Reader emotions (overall)\",  fontweight=\"bold\")\n",
    "axes[1].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[1].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[1].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[1].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], color=list(sns.color_palette())[3], alpha=0.2, label='Confidence Interval')\n",
    "axes[1].set_xlabel(r\"$k$\")\n",
    "axes[1].set_ylabel(None)\n",
    "general_group = author_overall\n",
    "\n",
    "lplot= sns.lineplot(data = eng_effects_combined.loc[general_group], x='Rank', y='Unstandardized Effect', hue=list(eng_effects_combined.loc[general_group].index.values), ax=axes[0], marker=\"o\", markersize=8)\n",
    "lplot.axhline(0, color='black', linewidth=2)\n",
    "\n",
    "axes[0].legend(loc='lower left')\n",
    "axes[0].set_title(\"Author emotions (overall)\",  fontweight=\"bold\")\n",
    "axes[0].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[0]]], color=list(sns.color_palette())[0], alpha=0.2, label='Confidence Interval')\n",
    "axes[0].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[1]]], color=list(sns.color_palette())[1], alpha=0.2, label='Confidence Interval')\n",
    "axes[0].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[2]]], color=list(sns.color_palette())[2], alpha=0.2, label='Confidence Interval')\n",
    "axes[0].fill_between(rank, [eff[0] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], [eff[1] for eff in eng_effects_combined['Confidence Interval (unstandardized)'].loc[general_group[3]]], color=list(sns.color_palette())[3], alpha=0.2, label='Confidence Interval')\n",
    "axes[0].set_xlabel(r\"$k$\")\n",
    "axes[0].set_ylabel(r\"Average treatment effect with top $k$ tweets\")\n",
    "axes[0].set_yticks(np.arange(-.3, .31, .15))\n",
    "\n",
    "axes[0].margins(x=0)\n",
    "axes[1].margins(x=0)\n",
    "axes[2].margins(x=0)\n",
    "axes[3].margins(x=0)\n",
    "\n",
    "axes[0].grid(False)\n",
    "axes[1].grid(False)\n",
    "axes[2].grid(False)\n",
    "axes[3].grid(False)\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.savefig(f\"{FIG_FOLDER}/emotion_effects.pdf\", bbox_inches='tight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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