From 42e8fc8bce8c8f540e22680ea6c764ec0c875d75 Mon Sep 17 00:00:00 2001 From: priyankaiitg Date: Mon, 29 May 2023 20:41:02 +0530 Subject: [PATCH] Updated Python Notebook with Visualizations such as Heatmaps, Grouped Bloxplots and Grouped Barcharts to analyze the Sentiment across Genders estimated from First Name on Mailing Lists --- .../Sentiment Across Genders.ipynb | 860 ++++++++++++++++++ .../Sentiment Acrross Genders.ipynb | 477 ---------- 2 files changed, 860 insertions(+), 477 deletions(-) create mode 100644 examples/name-and-gender/Sentiment Across Genders.ipynb delete mode 100644 examples/name-and-gender/Sentiment Acrross Genders.ipynb diff --git a/examples/name-and-gender/Sentiment Across Genders.ipynb b/examples/name-and-gender/Sentiment Across Genders.ipynb new file mode 100644 index 0000000..fc07ccb --- /dev/null +++ b/examples/name-and-gender/Sentiment Across Genders.ipynb @@ -0,0 +1,860 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Extracting the sentiment versus estimated gender of participants on the mailing list. \n", + "\n", + "Disclaimer: BigBang uses a library that guesses the gender of a person based on their first name and census records. We understand that this method is prone to error. Only names with very high correlation with a particular gender are so identified. Because of these and other errors, we consider gender in statistical aggregates only. Please do not take these results as attributing gender to any particular individual on the mailing list." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Import the BigBang modules as needed. These should be in your Python environment if you've installed BigBang correctly.\n", + "\n", + "For sentiment analysis, we are using a pretrained python library, TextBlob, which we have tested is relatively fast." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_5637/1012371525.py:9: DeprecationWarning: the imp module is deprecated in favour of importlib and slated for removal in Python 3.12; see the module's documentation for alternative uses\n", + " import imp\n" + ] + } + ], + "source": [ + "import bigbang.ingress.mailman as mailman\n", + "import bigbang.analysis.graph as graph\n", + "import bigbang.analysis.process as process\n", + "from bigbang.parse import get_date\n", + "from bigbang.archive import Archive\n", + "from bigbang.archive import load as load_archive\n", + "import bigbang.analysis.utils as analysis_utils\n", + "\n", + "import imp\n", + "imp.reload(process)\n", + "\n", + "import pandas as pd\n", + "import datetime\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sb\n", + "import numpy as np\n", + "import math\n", + "import pytz\n", + "import pickle\n", + "import os\n", + "\n", + "from bigbang import parse\n", + "from gender_detector import gender_detector as gd\n", + "\n", + "from textblob import TextBlob" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now let's load the data for analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "stem = False\n", + "\n", + "\n", + "import os \n", + "cwd = os.getcwd() \n", + "\n", + "archives_names = [\"httpbisa\"]\n", + "\n", + "\n", + "archive_paths = list()\n", + "for archive_name in archives_names:\n", + " archive_paths.append('../archives/'+archive_name+'.csv')\n", + " \n", + "\n", + "archives_list = [load_archive(arch_path).data for arch_path in archive_paths]\n", + " \n", + "archives = Archive(pd.concat(archives_list))\n", + "archives_data = archives.data\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For each of our lists, we'll clean up the names, find the first name if there is one, and guess its gender. Pandas groups the data together for comparison. We keep count of the names we find that are ambiguous, for the next step." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "detector = gd.GenderDetector('us')\n", + "\n", + "\n", + "def guess_gender(name):\n", + " if not name:\n", + " return 'name unknown'\n", + " try:\n", + " if detector.guess(name) == 'unknown':\n", + " return 'gender unknown'\n", + " \n", + " return detector.guess(name)\n", + " except:\n", + " return 'error'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Instead of estimating the gender again for recipients, we lookup in the senders list itself whose gender estimates have been populated" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "def lookup_index(df, mdf, val, field = 'From Gender'):\n", + " vidx = df[df.index == val]\n", + " if vidx.empty :\n", + " return None\n", + " else :\n", + " #print(vidx.index.values[0])\n", + " midx = mdf[mdf.index == vidx.index.values[0]]\n", + " #print(midx.head())\n", + " #print(midx.index)\n", + " if midx.empty :\n", + " return None\n", + " else :\n", + " return midx[field].values[0]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "To process the data, we firstly drop rows that have missing information. Then we calculate the sentiment polarity of each email body, which signifies the sentiment posed by the sender, i.e., From, to the recipient, i.e., the In-Reply-To. Thereafter, the first name of the sender is guessed which is used to guess their gender and thereafter, the gender of the recipients. Finally, we drop rows that we were not able to process." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "mod_data = archives_data.dropna()\n", + "mod_data = mod_data[mod_data['In-Reply-To'] != 'None']\n", + "#mod_data = mod_data.head(30)\n", + "mod_data['Sentiment'] = mod_data['Body'].map(lambda x: TextBlob(x).sentiment.polarity)\n", + "mod_data['From Name'] = mod_data['From'].map(lambda x: parse.clean_from(x))\n", + "mod_data['From First Name'] = mod_data['From Name'].map(lambda x: parse.guess_first_name(x))\n", + "mod_data['From Gender'] = mod_data['From First Name'].map(guess_gender)\n", + "mod_data['InReplyTo Gender'] = mod_data['In-Reply-To'].map(lambda x: lookup_index(archives_data, mod_data,x))\n", + "mod_data = mod_data.dropna()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The number of emails that were present in the mailing list archive is usually larger than the number of emails we could process primarily due to the limitations in coverage of guessing gender from first names. We shall attempt to improve this coverage using psycholinguistic tools forthwith." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "25796" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mod_data['From'].size" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "40147" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "archives_data['From'].size" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Relevant statistics need to be printed to understand the participation of men and women in the mailing list. We sum up the number of emails from a particular sender, to remove duplicates. Thereafter, we print and plot the number of total emails and unique men, women senders, recipients as well as communication across and within genders." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### The number of people of each gender sent and received emails to people of each gender" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_5637/2884405722.py:1: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.\n", + " tempdata = mod_data.groupby(['From Gender','InReplyTo Gender','From'], as_index=False)['From','Subject'].count()\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tempdata = mod_data.groupby(['From Gender','InReplyTo Gender','From'], as_index=False)['From','Subject'].count()\n", + "\n", + "tempdata = pd.DataFrame(tempdata)\n", + "\n", + "unique_interaction = pd.DataFrame(tempdata.groupby(['From Gender', 'InReplyTo Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(unique_interaction)\n", + "\n", + "sb.set_theme(style=\"white\")\n", + "\n", + "# Set up the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(8, 5))\n", + "\n", + "# Compute the correlation matrix\n", + "ui_corr = unique_interaction.pivot(index='From Gender',columns='InReplyTo Gender', values='Count')\n", + "\n", + "# Generate a custom diverging colormap\n", + "cmap = sb.diverging_palette(230, 20, as_cmap=True)\n", + "\n", + "# Draw the heatmap with the correct aspect ratio\n", + "sb.heatmap(ui_corr,cmap=cmap,annot=True,fmt=\".0f\",\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### The number of people of each gender who sent or received emails in total " + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "unique_senders = pd.DataFrame(tempdata.groupby(['From Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(unique_senders)\n", + "\n", + "\n", + "unique_receivers = pd.DataFrame(tempdata.groupby(['InReplyTo Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(unique_receivers)\n", + "\n", + "\n", + "sb.set_theme(style=\"whitegrid\")\n", + "\n", + "# Initialize the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(7, 5))\n", + "\n", + "# Plot the unique senders\n", + "sb.set_color_codes(\"muted\")\n", + "sb.barplot(x=\"From Gender\", y=\"Count\", data=unique_senders,\n", + " label=\"Unique Senders\", color=\"b\")\n", + "\n", + "# Plot the unique receivers\n", + "sb.set_color_codes(\"pastel\")\n", + "sb.barplot(x=\"InReplyTo Gender\", y=\"Count\", data=unique_receivers,\n", + " label=\"Unique Receivers\", color=\"b\")\n", + "\n", + "\n", + "# Add a legend and informative axis label\n", + "ax.legend(ncol=1, loc=\"upper left\", frameon=True)\n", + "ax.set(ylabel=\"Count\",\n", + " xlabel=\"Unique senders and receivers of each Gender\")\n", + "sb.despine(left=True, bottom=True)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Response or interaction ratio of people of each gender towards each gender" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "unique_replies_by_gender = tempdata.groupby('From Gender').count()['Subject']\n", + "\n", + "unique_replied_by_gender = tempdata.groupby(['From Gender', 'InReplyTo Gender']).count()['Subject']\n", + "\n", + "\n", + "unique_interaction_ratio= (unique_replied_by_gender/unique_replies_by_gender).unstack()\n", + "#print(unique_interaction_ratio)\n", + "\n", + "sb.set_theme(style=\"white\")\n", + "\n", + "# Set up the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(8, 5))\n", + "\n", + "# Generate a custom diverging colormap\n", + "cmap = sb.diverging_palette(230, 20, as_cmap=True)\n", + "\n", + "# Draw the heatmap with the correct aspect ratio\n", + "sb.heatmap(unique_interaction_ratio,cmap=cmap,annot=True,fmt=\".6f\",\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Number of emails in total sent or received by each gender to each gender" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nonunique_interaction = pd.DataFrame(mod_data.groupby(['From Gender', 'InReplyTo Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(nonunique_interaction)\n", + "\n", + "sb.set_theme(style=\"white\")\n", + "\n", + "# Set up the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(8, 5))\n", + "\n", + "# Compute the correlation matrix\n", + "nui_corr = nonunique_interaction.pivot(index='From Gender',columns='InReplyTo Gender', values='Count')\n", + "\n", + "# Generate a custom diverging colormap\n", + "cmap = sb.diverging_palette(230, 20, as_cmap=True)\n", + "\n", + "# Draw the heatmap with the correct aspect ratio\n", + "sb.heatmap(nui_corr,cmap=cmap,annot=True,fmt=\".0f\",\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Total emails sent or received by each gender" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nonunique_senders = pd.DataFrame(mod_data.groupby(['From Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(nonunique_senders)\n", + "\n", + "nonunique_receivers = pd.DataFrame(mod_data.groupby(['InReplyTo Gender'],\n", + " as_index=False)['From'].count()).rename(columns={'From':'Count'})\n", + "\n", + "#print(nonunique_receivers)\n", + "\n", + "\n", + "sb.set_theme(style=\"whitegrid\")\n", + "\n", + "# Initialize the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(7, 5))\n", + "\n", + "# Plot the non unique senders\n", + "sb.set_color_codes(\"muted\")\n", + "sb.barplot(x=\"From Gender\", y=\"Count\", data=nonunique_senders,\n", + " label=\"Non Unique Senders\", color=\"b\")\n", + "\n", + "# Plot the non unique receivers\n", + "sb.set_color_codes(\"pastel\")\n", + "sb.barplot(x=\"InReplyTo Gender\", y=\"Count\", data=nonunique_receivers,\n", + " label=\"Non Unique Receivers\", color=\"b\")\n", + "\n", + "\n", + "# Add a legend and informative axis label\n", + "ax.legend(ncol=1, loc=\"upper left\", frameon=True)\n", + "ax.set(ylabel=\"Count\",\n", + " xlabel=\"Non Unique senders and receivers of each Gender\")\n", + "sb.despine(left=True, bottom=True)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Response or interaction ratio of total emails sent or received by each gender" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nonunique_replies_by_gender = mod_data.groupby('From Gender').count()['Subject']\n", + "nonunique_replied_by_gender = mod_data.groupby(['From Gender', 'InReplyTo Gender']).count()['Subject']\n", + "\n", + "nonunique_interaction_ratio = (nonunique_replied_by_gender/nonunique_replies_by_gender).unstack()\n", + "\n", + "#print(nonunique_interaction_ratio)\n", + "\n", + "sb.set_theme(style=\"white\")\n", + "\n", + "# Set up the matplotlib figure\n", + "f, ax = plt.subplots(figsize=(11, 9))\n", + "\n", + "# Generate a custom diverging colormap\n", + "cmap = sb.diverging_palette(230, 20, as_cmap=True)\n", + "\n", + "# Draw the heatmap with the correct aspect ratio\n", + "sb.heatmap(nonunique_interaction_ratio,cmap=cmap,annot=True,fmt=\".6f\",\n", + " square=True, linewidths=.5, cbar_kws={\"shrink\": .5})\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Finally we also identify the sentiment polarity statistics such as minimum, maximum, average, total, variance and standard deviation across and within genders in the mailing list. This gives us an overview of the tone of communication vis a vis gender in the mailing list. " + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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meanvarmaxmin
From GenderInReplyTo Gender
errorerror0.154949NaN0.1549490.154949
gender unknown0.0943830.0047530.1731480.045000
male0.1592250.0020180.2296050.065530
femalefemale0.0518780.0095530.156558-0.114744
gender unknown0.1431080.0109010.500000-0.087662
male0.1429180.0131340.533333-0.121667
name unknown0.0658120.0083600.204762-0.090000
gender unknownerror0.1297210.0030000.1866670.077412
female0.1734230.0132270.557143-0.050000
gender unknown0.1501300.0163350.750000-0.750000
male0.1567820.0167871.000000-1.000000
name unknown0.1509900.0134780.766667-0.205556
maleerror0.1435230.0056280.3401790.047436
female0.1261700.0192880.750000-0.462500
gender unknown0.1266980.0140961.000000-0.700000
male0.1237600.0109050.800000-0.750000
name unknown0.1254710.0111081.000000-0.175000
\n", + "
" + ], + "text/plain": [ + " mean var max min\n", + "From Gender InReplyTo Gender \n", + "error error 0.154949 NaN 0.154949 0.154949\n", + " gender unknown 0.094383 0.004753 0.173148 0.045000\n", + " male 0.159225 0.002018 0.229605 0.065530\n", + "female female 0.051878 0.009553 0.156558 -0.114744\n", + " gender unknown 0.143108 0.010901 0.500000 -0.087662\n", + " male 0.142918 0.013134 0.533333 -0.121667\n", + " name unknown 0.065812 0.008360 0.204762 -0.090000\n", + "gender unknown error 0.129721 0.003000 0.186667 0.077412\n", + " female 0.173423 0.013227 0.557143 -0.050000\n", + " gender unknown 0.150130 0.016335 0.750000 -0.750000\n", + " male 0.156782 0.016787 1.000000 -1.000000\n", + " name unknown 0.150990 0.013478 0.766667 -0.205556\n", + "male error 0.143523 0.005628 0.340179 0.047436\n", + " female 0.126170 0.019288 0.750000 -0.462500\n", + " gender unknown 0.126698 0.014096 1.000000 -0.700000\n", + " male 0.123760 0.010905 0.800000 -0.750000\n", + " name unknown 0.125471 0.011108 1.000000 -0.175000" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].agg(['mean','var','max','min','std'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### Distribution of Sentiment from men and women in the mailing list towards men and women" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sentiment_across_genders = mod_data[((mod_data['From Gender']=='male') \n", + " | (mod_data['From Gender']=='female'))\n", + " & ((mod_data['InReplyTo Gender']=='male') \n", + " | (mod_data['InReplyTo Gender']=='female'))]\n", + "\n", + "sb.set_theme(style=\"ticks\", palette=\"pastel\")\n", + "\n", + "# Draw a nested boxplot to show sentiment by each gender towards each gender\n", + "sb.boxplot(x=\"From Gender\", y=\"Sentiment\",\n", + " hue=\"InReplyTo Gender\", palette=[\"m\", \"g\"],\n", + " data=sentiment_across_genders)\n", + "sb.despine(offset=10, trim=True)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/examples/name-and-gender/Sentiment Acrross Genders.ipynb b/examples/name-and-gender/Sentiment Acrross Genders.ipynb deleted file mode 100644 index 66ff385..0000000 --- a/examples/name-and-gender/Sentiment Acrross Genders.ipynb +++ /dev/null @@ -1,477 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Extracting the sentiment versus estimated gender of participants on the mailing list. " - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Import the BigBang modules as needed. These should be in your Python environment if you've installed BigBang correctly." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/tmp/ipykernel_33443/3698918106.py:9: DeprecationWarning: the imp module is deprecated in favour of importlib and slated for removal in Python 3.12; see the module's documentation for alternative uses\n", - " import imp\n" - ] - } - ], - "source": [ - "import bigbang.ingress.mailman as mailman\n", - "import bigbang.analysis.graph as graph\n", - "import bigbang.analysis.process as process\n", - "from bigbang.parse import get_date\n", - "from bigbang.archive import Archive\n", - "from bigbang.archive import load as load_archive\n", - "import bigbang.analysis.utils as analysis_utils\n", - "\n", - "import imp\n", - "imp.reload(process)\n", - "\n", - "import pandas as pd\n", - "import datetime\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n", - "import math\n", - "import pytz\n", - "import pickle\n", - "import os\n", - "\n", - "from bigbang import parse\n", - "from gender_detector import gender_detector as gd\n", - "\n", - "from textblob import TextBlob" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's load the data for analysis." - ] - }, - { - "cell_type": "code", - "execution_count": 118, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "stem = False\n", - "\n", - "\n", - "import os \n", - "cwd = os.getcwd() \n", - "\n", - "archives_names = [\"httpbisa\"]\n", - "\n", - "\n", - "archive_paths = list()\n", - "for archive_name in archives_names:\n", - " archive_paths.append('../archives/'+archive_name+'.csv')\n", - " \n", - "\n", - "archives_list = [load_archive(arch_path).data for arch_path in archive_paths]\n", - " \n", - "archives = Archive(pd.concat(archives_list))\n", - "archives_data = archives.data\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "For each of our lists, we'll clean up the names, find the first name if there is one, and guess its gender. Pandas groups the data together for comparison. We keep count of the names we find that are ambiguous, for the next step." - ] - }, - { - "cell_type": "code", - "execution_count": 119, - "metadata": {}, - "outputs": [], - "source": [ - "detector = gd.GenderDetector('us')\n", - "\n", - "\n", - "def guess_gender(name):\n", - " if not name:\n", - " return 'name unknown'\n", - " try:\n", - " if detector.guess(name) == 'unknown':\n", - " return 'gender unknown'\n", - " \n", - " return detector.guess(name)\n", - " except:\n", - " return 'error'\n", - "\n", - "\n", - "def lookup_index(df, mdf, val, field = 'From Gender'):\n", - " #addr = analysis_utils.extract_email(val)\n", - " #if not addr:\n", - " # return 'email garbled'\n", - " #else:\n", - " #vidx = df[[analysis_utils.extract_email(e) in addr for e in df.index]]\n", - " vidx = df[df.index == val]\n", - " if vidx.empty :\n", - " return None\n", - " else :\n", - " #print(vidx.index.values[0])\n", - " midx = mdf[mdf.index == vidx.index.values[0]]\n", - " #print(midx.head())\n", - " #print(midx.index)\n", - " if midx.empty :\n", - " return None\n", - " else :\n", - " return midx[field].values[0]" - ] - }, - { - "cell_type": "code", - "execution_count": 120, - "metadata": {}, - "outputs": [], - "source": [ - "mod_data = archives_data.dropna()\n", - "mod_data = mod_data[mod_data['In-Reply-To'] != 'None']\n", - "#mod_data = mod_data.head(30)\n", - "mod_data['Sentiment'] = mod_data['Body'].map(lambda x: TextBlob(x).sentiment.polarity)\n", - "mod_data['From Name'] = mod_data['From'].map(lambda x: parse.clean_from(x))\n", - "mod_data['From First Name'] = mod_data['From Name'].map(lambda x: parse.guess_first_name(x))\n", - "mod_data['From Gender'] = mod_data['From First Name'].map(guess_gender)\n", - "mod_data['InReplyTo Gender'] = mod_data['In-Reply-To'].map(lambda x: lookup_index(archives_data, mod_data,x))\n", - "mod_data = mod_data.dropna()" - ] - }, - { - "cell_type": "code", - "execution_count": 121, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "25796" - ] - }, - "execution_count": 121, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "mod_data['From'].size" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "40147" - ] - }, - "execution_count": 122, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "archives_data['From'].size" - ] - }, - { - "cell_type": "code", - "execution_count": 123, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "328\n", - "150\n", - "16474\n", - "3423\n", - "323\n", - "270\n", - "15604\n", - "2202\n", - "190\n", - "75\n", - "183\n", - "195\n", - "10002\n", - "1566\n", - "6\n", - "12\n" - ] - } - ], - "source": [ - "#mod_data\n", - "#mod_data['In-Reply-To'].head().map(lambda x: lookup_index(archives_data,x))\n", - "\n", - "tempdata = mod_data.groupby(['From Gender','InReplyTo Gender','From'], as_index=False)['From'].count()\n", - "\n", - "tempdata = pd.DataFrame(tempdata)\n", - "#print(tempdata)\n", - "\n", - "#tempdata = mod_data.drop_duplicates('From')\n", - "\n", - "print(tempdata[tempdata['From Gender'] == 'female']['From'].sum())\n", - "\n", - "print(tempdata[tempdata['From Gender'] == 'female'].size)\n", - "\n", - "print(tempdata[tempdata['From Gender'] == 'male']['From'].sum())\n", - "\n", - "print(tempdata[tempdata['From Gender'] == 'male'].size)\n", - "\n", - "print(tempdata[tempdata['InReplyTo Gender'] == 'female']['From'].sum())\n", - "\n", - "print(tempdata[tempdata['InReplyTo Gender'] == 'female'].size)\n", - "\n", - "print(tempdata[tempdata['InReplyTo Gender'] == 'male']['From'].sum())\n", - "\n", - "print(tempdata[tempdata['InReplyTo Gender'] == 'male'].size)\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'female') & (tempdata['InReplyTo Gender'] == 'male')]['From'].sum())\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'female') & (tempdata['InReplyTo Gender'] == 'male')].size)\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'male') & (tempdata['InReplyTo Gender'] == 'female')]['From'].sum())\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'male') & (tempdata['InReplyTo Gender'] == 'female')].size)\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'male') & (tempdata['InReplyTo Gender'] == 'male')]['From'].sum())\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'male') & (tempdata['InReplyTo Gender'] == 'male')].size)\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'female') & (tempdata['InReplyTo Gender'] == 'female')]['From'].sum())\n", - "\n", - "print(tempdata[(tempdata['From Gender'] == 'female') & (tempdata['InReplyTo Gender'] == 'female')].size)" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Minimun Sentiment Expressed from one gender to another\n", - "From Gender InReplyTo Gender\n", - "error error 0.154949\n", - " gender unknown 0.045000\n", - " male 0.065530\n", - "female female -0.114744\n", - " gender unknown -0.087662\n", - " male -0.121667\n", - " name unknown -0.090000\n", - "gender unknown error 0.077412\n", - " female -0.050000\n", - " gender unknown -0.750000\n", - " male -1.000000\n", - " name unknown -0.205556\n", - "male error 0.047436\n", - " female -0.462500\n", - " gender unknown -0.700000\n", - " male -0.750000\n", - " name unknown -0.175000\n", - "Name: Sentiment, dtype: float64\n", - "=======\n", - "=======\n", - "Maximum Sentiment Polarity Expressed from one Gender to another\n", - "From Gender InReplyTo Gender\n", - "error error 0.154949\n", - " gender unknown 0.173148\n", - " male 0.229605\n", - "female female 0.156558\n", - " gender unknown 0.500000\n", - " male 0.533333\n", - " name unknown 0.204762\n", - "gender unknown error 0.186667\n", - " female 0.557143\n", - " gender unknown 0.750000\n", - " male 1.000000\n", - " name unknown 0.766667\n", - "male error 0.340179\n", - " female 0.750000\n", - " gender unknown 1.000000\n", - " male 0.800000\n", - " name unknown 1.000000\n", - "Name: Sentiment, dtype: float64\n", - "=======\n", - "=======\n", - "Sum of all sentiment polarity expressed from one Gender to another\n", - "From Gender InReplyTo Gender\n", - "error error 0.154949\n", - " gender unknown 0.283148\n", - " male 1.910701\n", - "female female 0.311267\n", - " gender unknown 17.745453\n", - " male 27.154412\n", - " name unknown 0.526495\n", - "gender unknown error 0.389164\n", - " female 23.238618\n", - " gender unknown 455.494570\n", - " male 846.624185\n", - " name unknown 61.453039\n", - "male error 1.865794\n", - " female 23.089044\n", - " gender unknown 674.537999\n", - " male 1237.845733\n", - " name unknown 119.448438\n", - "Name: Sentiment, dtype: float64\n", - "=======\n", - "=======\n", - "Average sentiment polarity expressed from one Gender to another\n", - "From Gender InReplyTo Gender\n", - "error error 0.154949\n", - " gender unknown 0.094383\n", - " male 0.159225\n", - "female female 0.051878\n", - " gender unknown 0.143108\n", - " male 0.142918\n", - " name unknown 0.065812\n", - "gender unknown error 0.129721\n", - " female 0.173423\n", - " gender unknown 0.150130\n", - " male 0.156782\n", - " name unknown 0.150990\n", - "male error 0.143523\n", - " female 0.126170\n", - " gender unknown 0.126698\n", - " male 0.123760\n", - " name unknown 0.125471\n", - "Name: Sentiment, dtype: float64\n", - "=======\n", - "=======\n", - "Standard Deviation in sentiment polarity expressed from one Gender to another\n", - "From Gender InReplyTo Gender\n", - "error error NaN\n", - " gender unknown 0.068942\n", - " male 0.044927\n", - "female female 0.097742\n", - " gender unknown 0.104407\n", - " male 0.114603\n", - " name unknown 0.091431\n", - "gender unknown error 0.054775\n", - " female 0.115008\n", - " gender unknown 0.127807\n", - " male 0.129566\n", - " name unknown 0.116095\n", - "male error 0.075020\n", - " female 0.138883\n", - " gender unknown 0.118727\n", - " male 0.104428\n", - " name unknown 0.105396\n", - "Name: Sentiment, dtype: float64\n", - "=======\n", - "=======\n", - "Variance in sentiment polarity expressed from one Gender to another\n", - "From Gender InReplyTo Gender\n", - "error error NaN\n", - " gender unknown 0.004753\n", - " male 0.002018\n", - "female female 0.009553\n", - " gender unknown 0.010901\n", - " male 0.013134\n", - " name unknown 0.008360\n", - "gender unknown error 0.003000\n", - " female 0.013227\n", - " gender unknown 0.016335\n", - " male 0.016787\n", - " name unknown 0.013478\n", - "male error 0.005628\n", - " female 0.019288\n", - " gender unknown 0.014096\n", - " male 0.010905\n", - " name unknown 0.011108\n", - "Name: Sentiment, dtype: float64\n", - "=======\n" - ] - } - ], - "source": [ - "print(\"Minimun Sentiment Expressed from one gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('min'))\n", - "print(\"=======\")\n", - "print(\"=======\")\n", - "print(\"Maximum Sentiment Polarity Expressed from one Gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('max'))\n", - "print(\"=======\")\n", - "print(\"=======\")\n", - "print(\"Sum of all sentiment polarity expressed from one Gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('sum'))\n", - "print(\"=======\")\n", - "print(\"=======\")\n", - "print(\"Average sentiment polarity expressed from one Gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('mean'))\n", - "print(\"=======\")\n", - "print(\"=======\")\n", - "print(\"Standard Deviation in sentiment polarity expressed from one Gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('std'))\n", - "print(\"=======\")\n", - "print(\"=======\")\n", - "print(\"Variance in sentiment polarity expressed from one Gender to another\")\n", - "print(mod_data.groupby(['From Gender', 'InReplyTo Gender'])['Sentiment'].aggregate('var'))\n", - "print(\"=======\")\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.3" - } - }, - "nbformat": 4, - "nbformat_minor": 1 -}