├── PPT_Presentation.pdf ├── Deception_Detection_Report.pdf ├── README.md ├── Deception_Data_Acquisition.ipynb ├── LICENSE └── Deception_Data_Cleaning_MORE_DATA.ipynb /PPT_Presentation.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Victor-Palacios/Deception_Detection_Capstone/HEAD/PPT_Presentation.pdf -------------------------------------------------------------------------------- /Deception_Detection_Report.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/Victor-Palacios/Deception_Detection_Capstone/HEAD/Deception_Detection_Report.pdf -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Deception Detection Summary 2 | 3 | ## Problem 1 4 | How does a liar's speech vary from a truth-teller? 5 | 6 | ## Approach for Problem 1 7 | ### Create features to analyze from raw statements: 8 | No. of characters 9 | 10 | No. of words 11 | 12 | Avg. length of words 13 | 14 | Readability score 15 | 16 | POS (part of speech): Is this word an adjective, noun, something else? 17 | 18 | NER (named entity recognition tagging): tags the kind of noun--person, place, organization, etc.--among other things 19 | 20 | SD (syntatic dependency): the relation between tokens 21 | 22 | ## Results of Problem 1 23 | 24 | ### Significantly higher for Truth 25 | Statement Count: Character & Word count 26 | 27 | General (15 tags) POS tagging: adj., conjunction+ (i.e., "of", "about", "to", etc.), noun, number, determiner (i.e., "a", "an", "the") 28 | 29 | Specific (52 tags) POS tagging: cardinal numbers, determiners, conjunctions(subordinating or preposition), adjective(comparative), noun(singular or mass) 30 | 31 | NER: references to dates, percentages, numbers 32 | 33 | SD: adjectival modifier, determiner, numeric modifier, object of preposition, prepositional modifier 34 | 35 | ### Significantly higher for Falsehoods 36 | Statement Length: Average word length 37 | 38 | Specific (52 tags) POS tagging: verb (modal auxiliary), superfluous punctuation 39 | 40 | NER: references to people 41 | 42 | SD: clausal complement, clausal subject 43 | 44 | ## Problem 2 45 | Can verbal deception be predicted with machine learning? 46 | 47 | ## Approach for Problem 2 48 | ### 5 datasets for machine learning 49 | The standard in natural language processing is to normalize text, i.e., distill content in statements by 50 | removing frequent words (i.e., stopwords), punctuation, etc. 51 | But, given the statistics from the data analysis revealed that the frequency of stopwords, punctuation, etc. 52 | varied with statistical difference in lies versus truth, 53 | I hypothesize that normalization may lower the ability for machine learning algorithms to predict deception. 54 | To test this hypothesis, I will compare the raw statements, 3 normalized permutations of the raw statements, 55 | and a dataframe composed of statistics about the raw statements (number of words, nouns, etc.) 56 | #### Raw statements 57 | The statements as they are (i.e., without any alteration) 58 | #### Lightly normalized statements 59 | Statement words were converted to lowercase, and the following were removed: 60 | whitespaces and html tags 61 | #### Lightly norm-lemmatized statements 62 | "Lightly normalized statements" were lemmatized 63 | #### Fully normalized statements 64 | "Lightly normalized and lemmatized statements" had the following removed: 65 | punctuation, stopwords, special characters 66 | #### Statistical Features 67 | In the exploratary analysis, over 100 features were created based on word count, number of nouns, etc.; 68 | this will be the basis for the final model that does not use statements, 69 | instead it uses statistics about the statements. 70 | 71 | ## Results of Problem 2 72 | ### Comparing the 5 datasets 73 | #### raw statements vs normalized statements 74 | performed best on train set (62% accuracy) : lightly normalized statements 75 | #### BoW, n-GRAM=1-4, TF-IDF 76 | performed comparably well on train set (62% accuracy) : n-gram size 1-2 and tfidf 77 | #### Multinomial Naive Bayes (mnb), Logistic Regression (lgr), Random Forests 78 | performed comparably well on train set (62% accuracy) : mnb and lgr 79 | #### Best accuracy on hold-out set from the above groups 80 | 57% accuracy on the hold-out set: lightly normalized statements, ngram_range = (1,2), mnb 81 | #### Engineered Features 82 | comparable results to the above: 57% accuracy on the hold out set using mnb 83 | -------------------------------------------------------------------------------- /Deception_Data_Acquisition.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "# Packages for Web-Scraping\n", 10 | "from requests import get\n", 11 | "from bs4 import BeautifulSoup\n", 12 | "from time import time\n", 13 | "from time import sleep\n", 14 | "from random import randint\n", 15 | "from IPython.core.display import clear_output\n", 16 | "from warnings import warn\n", 17 | "\n", 18 | "# Packages for Saving File after Scraping\n", 19 | "import numpy as np\n", 20 | "import pandas as pd" 21 | ] 22 | }, 23 | { 24 | "cell_type": "code", 25 | "execution_count": null, 26 | "metadata": {}, 27 | "outputs": [], 28 | "source": [ 29 | "# url 1st page info, response object, and sample\n", 30 | "url = 'https://www.politifact.com/truth-o-meter/statements/?page=1'\n", 31 | "response = get(url)\n", 32 | "print(response.text[:500])" 33 | ] 34 | }, 35 | { 36 | "cell_type": "code", 37 | "execution_count": null, 38 | "metadata": {}, 39 | "outputs": [], 40 | "source": [ 41 | "# 1st page BeautifulSoup object, confirm type\n", 42 | "html_soup = BeautifulSoup(response.text, 'html.parser')\n", 43 | "type(html_soup)" 44 | ] 45 | }, 46 | { 47 | "cell_type": "code", 48 | "execution_count": null, 49 | "metadata": {}, 50 | "outputs": [], 51 | "source": [ 52 | "# finding each row of data we want to scrape, confirm type, check length\n", 53 | "statement_containers = html_soup.find_all('div', class_ = 'scoretable__item')\n", 54 | "print(type(statement_containers))\n", 55 | "print(len(statement_containers))" 56 | ] 57 | }, 58 | { 59 | "cell_type": "code", 60 | "execution_count": null, 61 | "metadata": {}, 62 | "outputs": [], 63 | "source": [ 64 | "# checking data\n", 65 | "s = statement_containers[1]\n", 66 | "s" 67 | ] 68 | }, 69 | { 70 | "cell_type": "code", 71 | "execution_count": null, 72 | "metadata": {}, 73 | "outputs": [], 74 | "source": [ 75 | "# statement\n", 76 | "s.find('p', class_ = 'statement__text').get_text(strip=True)" 77 | ] 78 | }, 79 | { 80 | "cell_type": "code", 81 | "execution_count": null, 82 | "metadata": {}, 83 | "outputs": [], 84 | "source": [ 85 | "# statement source\n", 86 | "s.find('div', class_ = 'statement__source').get_text(strip=True)" 87 | ] 88 | }, 89 | { 90 | "cell_type": "code", 91 | "execution_count": null, 92 | "metadata": {}, 93 | "outputs": [], 94 | "source": [ 95 | "# statement link\n", 96 | "s.find('p', class_ = 'statement__text').a[\"href\"]" 97 | ] 98 | }, 99 | { 100 | "cell_type": "code", 101 | "execution_count": null, 102 | "metadata": {}, 103 | "outputs": [], 104 | "source": [ 105 | "# statement veracity\n", 106 | "s.img[\"alt\"]" 107 | ] 108 | }, 109 | { 110 | "cell_type": "code", 111 | "execution_count": null, 112 | "metadata": {}, 113 | "outputs": [], 114 | "source": [ 115 | "# Lists to store the scraped data in\n", 116 | "statement = []\n", 117 | "source = []\n", 118 | "link = []\n", 119 | "veracity = []\n", 120 | "\n", 121 | "# Extract data from individual container\n", 122 | "for container in statement_containers:\n", 123 | "# statement\n", 124 | " sta = container.find('p', class_ = 'statement__text').get_text(strip=True)\n", 125 | " statement.append(sta)\n", 126 | "# source\n", 127 | " sou = container.find('div', class_ = 'statement__source').get_text(strip=True)\n", 128 | " source.append(sou)\n", 129 | "# link\n", 130 | " lin = container.find('p', class_ = 'statement__text').a[\"href\"]\n", 131 | " link.append(lin)\n", 132 | "# veracity\n", 133 | " ver = container.img[\"alt\"]\n", 134 | " veracity.append(ver)" 135 | ] 136 | }, 137 | { 138 | "cell_type": "code", 139 | "execution_count": null, 140 | "metadata": {}, 141 | "outputs": [], 142 | "source": [ 143 | "# 1st page df\n", 144 | "test_df = pd.DataFrame(\n", 145 | " {'statement': statement,\n", 146 | " 'source': source,\n", 147 | " 'link': link,\n", 148 | " 'veracity': veracity\n", 149 | "})\n", 150 | "print(test_df.info())\n", 151 | "test_df" 152 | ] 153 | }, 154 | { 155 | "cell_type": "code", 156 | "execution_count": null, 157 | "metadata": {}, 158 | "outputs": [], 159 | "source": [ 160 | "# Testing 5 pages\n", 161 | "pages = [str(i) for i in range(1,5)]\n", 162 | "start_time = time()\n", 163 | "requests = 0\n", 164 | "for _ in range(5):\n", 165 | "# request goes here\n", 166 | " requests += 1\n", 167 | " sleep(randint(1,3))\n", 168 | " current_time = time()\n", 169 | " elapsed_time = current_time - start_time\n", 170 | " print('Request: {}; Frequency: {} requests/s'.format(requests, requests/elapsed_time))\n", 171 | " clear_output(wait = True)" 172 | ] 173 | }, 174 | { 175 | "cell_type": "code", 176 | "execution_count": null, 177 | "metadata": {}, 178 | "outputs": [], 179 | "source": [ 180 | "# If above is problem-free, proceed to scrape all pages\n", 181 | "# Scraping 834 pages takes about 4-5 hours\n", 182 | "\n", 183 | "# Lists to store all the scraped data in\n", 184 | "statement = []\n", 185 | "source = []\n", 186 | "link = []\n", 187 | "veracity = []\n", 188 | "\n", 189 | "# Preparing the monitoring of the loop\n", 190 | "start_time = time()\n", 191 | "requests = 0\n", 192 | "\n", 193 | "# For every page in the interval\n", 194 | "pages = [str(i) for i in range(1,834)]\n", 195 | "for page in pages:\n", 196 | "\n", 197 | " # Make a get request\n", 198 | " response = get('https://www.politifact.com/truth-o-meter/statements/?page=' + page)\n", 199 | "\n", 200 | " # Pause the loop in random intervals so your IP address doesn't get banned\n", 201 | " sleep(randint(8,15))\n", 202 | "\n", 203 | " # Monitor the requests\n", 204 | " requests += 1\n", 205 | " elapsed_time = time() - start_time\n", 206 | " print('Request:{}; Frequency: {} requests/s'.format(requests, requests/elapsed_time))\n", 207 | " clear_output(wait = True)\n", 208 | "\n", 209 | " # Throw a warning for non-200 status codes\n", 210 | " if response.status_code != 200:\n", 211 | " warn('Request: {}; Status code: {}'.format(requests, response.status_code))\n", 212 | "\n", 213 | " # Parse the content of the request with BeautifulSoup\n", 214 | " page_html = BeautifulSoup(response.text, 'html.parser')\n", 215 | "\n", 216 | " # Select all the containers from a single page\n", 217 | " statement_containers = page_html.find_all('div', class_ = 'scoretable__item')\n", 218 | "\n", 219 | " for container in statement_containers:\n", 220 | " # statement\n", 221 | " sta = container.find('p', class_ = 'statement__text').get_text(strip=True)\n", 222 | " statement.append(sta)\n", 223 | " # source\n", 224 | " sou = container.find('div', class_ = 'statement__source').get_text(strip=True)\n", 225 | " source.append(sou)\n", 226 | " # link\n", 227 | " lin = container.find('p', class_ = 'statement__text').a[\"href\"]\n", 228 | " link.append(lin)\n", 229 | " # veracity\n", 230 | " ver = container.img[\"alt\"]\n", 231 | " veracity.append(ver)" 232 | ] 233 | }, 234 | { 235 | "cell_type": "code", 236 | "execution_count": null, 237 | "metadata": {}, 238 | "outputs": [], 239 | "source": [ 240 | "# make a dataframe\n", 241 | "politifact_df = pd.DataFrame(\n", 242 | " {'statement': statement,\n", 243 | " 'source': source,\n", 244 | " 'link': link,\n", 245 | " 'veracity': veracity\n", 246 | "})\n", 247 | "print(politifact_df.info())\n", 248 | "politifact_df.tail(2)" 249 | ] 250 | }, 251 | { 252 | "cell_type": "code", 253 | "execution_count": null, 254 | "metadata": {}, 255 | "outputs": [], 256 | "source": [ 257 | "# save dataframe to csv\n", 258 | "politifact_df.to_csv('politifact.csv')" 259 | ] 260 | }, 261 | { 262 | "cell_type": "code", 263 | "execution_count": null, 264 | "metadata": {}, 265 | "outputs": [], 266 | "source": [ 267 | "# Tutorial followed to create this scraper: \n", 268 | "# https://www.dataquest.io/blog/web-scraping-beautifulsoup/" 269 | ] 270 | } 271 | ], 272 | "metadata": { 273 | "kernelspec": { 274 | "display_name": "Python 3", 275 | "language": "python", 276 | "name": "python3" 277 | }, 278 | "language_info": { 279 | "codemirror_mode": { 280 | "name": "ipython", 281 | "version": 3 282 | }, 283 | "file_extension": ".py", 284 | 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /Deception_Data_Cleaning_MORE_DATA.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "# Packages for Data Wrangling\n", 10 | "import numpy as np\n", 11 | "import pandas as pd\n", 12 | "import os\n", 13 | "import re\n", 14 | "from collections import Counter\n", 15 | "\n", 16 | "# For graphs\n", 17 | "import matplotlib as mpl\n", 18 | "import matplotlib.pyplot as plt\n", 19 | "import seaborn as sns" 20 | ] 21 | }, 22 | { 23 | "cell_type": "code", 24 | "execution_count": 2, 25 | "metadata": {}, 26 | "outputs": [], 27 | "source": [ 28 | "# Use cleaner absolute path to find file\n", 29 | "path = os.path.abspath('politifact.csv')\n", 30 | "df = pd.read_csv(path, index_col=0)" 31 | ] 32 | }, 33 | { 34 | "cell_type": "code", 35 | "execution_count": 3, 36 | "metadata": {}, 37 | "outputs": [ 38 | { 39 | "name": "stdout", 40 | "output_type": "stream", 41 | "text": [ 42 | "\n", 43 | "Int64Index: 16611 entries, 0 to 16610\n", 44 | "Data columns (total 4 columns):\n", 45 | " # Column Non-Null Count Dtype \n", 46 | "--- ------ -------------- ----- \n", 47 | " 0 statement 16611 non-null object\n", 48 | " 1 source 16611 non-null object\n", 49 | " 2 link 16611 non-null object\n", 50 | " 3 veracity 16611 non-null object\n", 51 | "dtypes: object(4)\n", 52 | "memory usage: 648.9+ KB\n" 53 | ] 54 | } 55 | ], 56 | "source": [ 57 | "# Check for null values and total number of rows\n", 58 | "df.info()" 59 | ] 60 | }, 61 | { 62 | "cell_type": "markdown", 63 | "metadata": {}, 64 | "source": [ 65 | "# Initially 16611 rows of non-null data" 66 | ] 67 | }, 68 | { 69 | "cell_type": "code", 70 | "execution_count": 4, 71 | "metadata": {}, 72 | "outputs": [ 73 | { 74 | "data": { 75 | "text/html": [ 76 | "
\n", 77 | "\n", 90 | "\n", 91 | " \n", 92 | " \n", 93 | " \n", 94 | " \n", 95 | " \n", 96 | " \n", 97 | " \n", 98 | " \n", 99 | " \n", 100 | " \n", 101 | " \n", 102 | " \n", 103 | " \n", 104 | " \n", 105 | " \n", 106 | " \n", 107 | " \n", 108 | " \n", 109 | " \n", 110 | " \n", 111 | " \n", 112 | " \n", 113 | " \n", 114 | " \n", 115 | " \n", 116 | " \n", 117 | " \n", 118 | " \n", 119 | " \n", 120 | " \n", 121 | " \n", 122 | " \n", 123 | "
statementsourcelinkveracity
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/Pants on Fire!
1Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\"Viral image/facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/False
2\"General Motors is making record profits.\"Glenn Kage/missouri/statements/2019/oct/25/glenn-kage/general-motors-profits-have-been-record-setting-no/Half-True
\n", 124 | "
" 125 | ], 126 | "text/plain": [ 127 | " statement \\\n", 128 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 129 | "1 Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\" \n", 130 | "2 \"General Motors is making record profits.\" \n", 131 | "\n", 132 | " source \\\n", 133 | "0 Facebook posts \n", 134 | "1 Viral image \n", 135 | "2 Glenn Kage \n", 136 | "\n", 137 | " link \\\n", 138 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 139 | "1 /facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/ \n", 140 | "2 /missouri/statements/2019/oct/25/glenn-kage/general-motors-profits-have-been-record-setting-no/ \n", 141 | "\n", 142 | " veracity \n", 143 | "0 Pants on Fire! \n", 144 | "1 False \n", 145 | "2 Half-True " 146 | ] 147 | }, 148 | "execution_count": 4, 149 | "metadata": {}, 150 | "output_type": "execute_result" 151 | } 152 | ], 153 | "source": [ 154 | "# to see statement in full\n", 155 | "pd.set_option('display.max_colwidth', 200) \n", 156 | "\n", 157 | "# See sample of data\n", 158 | "df.head(3)" 159 | ] 160 | }, 161 | { 162 | "cell_type": "code", 163 | "execution_count": 5, 164 | "metadata": {}, 165 | "outputs": [ 166 | { 167 | "data": { 168 | "text/plain": [ 169 | "False 3274\n", 170 | "Half-True 3158\n", 171 | "Mostly True 3010\n", 172 | "Mostly False 2756\n", 173 | "True 2340\n", 174 | "Pants on Fire! 1817\n", 175 | "Full Flop 159\n", 176 | "Half Flip 70\n", 177 | "No Flip 27\n", 178 | "Name: veracity, dtype: int64" 179 | ] 180 | }, 181 | "execution_count": 5, 182 | "metadata": {}, 183 | "output_type": "execute_result" 184 | } 185 | ], 186 | "source": [ 187 | "# check groups that exist in veracity column\n", 188 | "df.veracity.value_counts()" 189 | ] 190 | }, 191 | { 192 | "cell_type": "code", 193 | "execution_count": 6, 194 | "metadata": {}, 195 | "outputs": [ 196 | { 197 | "data": { 198 | "text/html": [ 199 | "
\n", 200 | "\n", 213 | "\n", 214 | " \n", 215 | " \n", 216 | " \n", 217 | " \n", 218 | " \n", 219 | " \n", 220 | " \n", 221 | " \n", 222 | " \n", 223 | " \n", 224 | " \n", 225 | " \n", 226 | " \n", 227 | " \n", 228 | " \n", 229 | " \n", 230 | " \n", 231 | " \n", 232 | " \n", 233 | " \n", 234 | " \n", 235 | " \n", 236 | " \n", 237 | " \n", 238 | " \n", 239 | " \n", 240 | " \n", 241 | " \n", 242 | " \n", 243 | " \n", 244 | " \n", 245 | " \n", 246 | "
statementsourcelinkveracity
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/Pants on Fire!
1Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\"Viral image/facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/False
3\"14,000 abandoned wind turbines litter the United States.\"Chain email/missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/Pants on Fire!
\n", 247 | "
" 248 | ], 249 | "text/plain": [ 250 | " statement \\\n", 251 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 252 | "1 Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\" \n", 253 | "3 \"14,000 abandoned wind turbines litter the United States.\" \n", 254 | "\n", 255 | " source \\\n", 256 | "0 Facebook posts \n", 257 | "1 Viral image \n", 258 | "3 Chain email \n", 259 | "\n", 260 | " link \\\n", 261 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 262 | "1 /facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/ \n", 263 | "3 /missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/ \n", 264 | "\n", 265 | " veracity \n", 266 | "0 Pants on Fire! \n", 267 | "1 False \n", 268 | "3 Pants on Fire! " 269 | ] 270 | }, 271 | "execution_count": 6, 272 | "metadata": {}, 273 | "output_type": "execute_result" 274 | } 275 | ], 276 | "source": [ 277 | "# Full Flop, Half Flip, & No Flip have nothing to do with veracity; remove them\n", 278 | "# Half-True doesn't help as it contains equal parts lie and truth\n", 279 | "\n", 280 | "ver_df = df[~df.isin(['Full Flop',\n", 281 | " 'Half Flip',\n", 282 | " 'No Flip',\n", 283 | " 'Half-True']).any(axis=1)]\n", 284 | "\n", 285 | "ver_df.head(3)" 286 | ] 287 | }, 288 | { 289 | "cell_type": "code", 290 | "execution_count": 7, 291 | "metadata": {}, 292 | "outputs": [ 293 | { 294 | "data": { 295 | "text/html": [ 296 | "
\n", 297 | "\n", 310 | "\n", 311 | " \n", 312 | " \n", 313 | " \n", 314 | " \n", 315 | " \n", 316 | " \n", 317 | " \n", 318 | " \n", 319 | " \n", 320 | " \n", 321 | " \n", 322 | " \n", 323 | " \n", 324 | " \n", 325 | " \n", 326 | " \n", 327 | " \n", 328 | " \n", 329 | " \n", 330 | " \n", 331 | " \n", 332 | " \n", 333 | " \n", 334 | " \n", 335 | " \n", 336 | " \n", 337 | " \n", 338 | " \n", 339 | " \n", 340 | " \n", 341 | " \n", 342 | " \n", 343 | "
statementsourcelinkveracity
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/0
1Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\"Viral image/facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/0
3\"14,000 abandoned wind turbines litter the United States.\"Chain email/missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/0
\n", 344 | "
" 345 | ], 346 | "text/plain": [ 347 | " statement \\\n", 348 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 349 | "1 Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\" \n", 350 | "3 \"14,000 abandoned wind turbines litter the United States.\" \n", 351 | "\n", 352 | " source \\\n", 353 | "0 Facebook posts \n", 354 | "1 Viral image \n", 355 | "3 Chain email \n", 356 | "\n", 357 | " link \\\n", 358 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 359 | "1 /facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/ \n", 360 | "3 /missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/ \n", 361 | "\n", 362 | " veracity \n", 363 | "0 0 \n", 364 | "1 0 \n", 365 | "3 0 " 366 | ] 367 | }, 368 | "execution_count": 7, 369 | "metadata": {}, 370 | "output_type": "execute_result" 371 | } 372 | ], 373 | "source": [ 374 | "# Transform variables into binary True/False\n", 375 | "ver_df = ver_df.replace({\"False\" : 0,\n", 376 | " \"Half-True\" : 1,\n", 377 | " \"Mostly True\" : 1,\n", 378 | " \"Mostly False\" : 0,\n", 379 | " \"True\" : 1,\n", 380 | " \"Pants on Fire!\" : 0\n", 381 | " })\n", 382 | "\n", 383 | "ver_df.head(3)" 384 | ] 385 | }, 386 | { 387 | "cell_type": "code", 388 | "execution_count": 8, 389 | "metadata": {}, 390 | "outputs": [ 391 | { 392 | "name": "stdout", 393 | "output_type": "stream", 394 | "text": [ 395 | "\n", 396 | "Int64Index: 13197 entries, 0 to 16610\n", 397 | "Data columns (total 4 columns):\n", 398 | " # Column Non-Null Count Dtype \n", 399 | "--- ------ -------------- ----- \n", 400 | " 0 statement 13197 non-null object\n", 401 | " 1 source 13197 non-null object\n", 402 | " 2 link 13197 non-null object\n", 403 | " 3 veracity 13197 non-null int64 \n", 404 | "dtypes: int64(1), object(3)\n", 405 | "memory usage: 515.5+ KB\n" 406 | ] 407 | } 408 | ], 409 | "source": [ 410 | "ver_df.info()" 411 | ] 412 | }, 413 | { 414 | "cell_type": "markdown", 415 | "metadata": {}, 416 | "source": [ 417 | "# By removing irrelevant statements, 13197 rows survive" 418 | ] 419 | }, 420 | { 421 | "cell_type": "code", 422 | "execution_count": 9, 423 | "metadata": {}, 424 | "outputs": [ 425 | { 426 | "data": { 427 | "text/plain": [ 428 | "0 7847\n", 429 | "1 5350\n", 430 | "Name: veracity, dtype: int64" 431 | ] 432 | }, 433 | "execution_count": 9, 434 | "metadata": {}, 435 | "output_type": "execute_result" 436 | } 437 | ], 438 | "source": [ 439 | "# check imbalance\n", 440 | "ver_df.veracity.value_counts()" 441 | ] 442 | }, 443 | { 444 | "cell_type": "code", 445 | "execution_count": 10, 446 | "metadata": { 447 | "scrolled": false 448 | }, 449 | "outputs": [ 450 | { 451 | "data": { 452 | "text/html": [ 453 | "
\n", 454 | "\n", 467 | "\n", 468 | " \n", 469 | " \n", 470 | " \n", 471 | " \n", 472 | " \n", 473 | " \n", 474 | " \n", 475 | " \n", 476 | " \n", 477 | " \n", 478 | " \n", 479 | " \n", 480 | " \n", 481 | " \n", 482 | " \n", 483 | " \n", 484 | " \n", 485 | " \n", 486 | " \n", 487 | " \n", 488 | " \n", 489 | " \n", 490 | " \n", 491 | " \n", 492 | " \n", 493 | " \n", 494 | " \n", 495 | " \n", 496 | " \n", 497 | " \n", 498 | " \n", 499 | " \n", 500 | " \n", 501 | " \n", 502 | " \n", 503 | " \n", 504 | " \n", 505 | " \n", 506 | " \n", 507 | " \n", 508 | " \n", 509 | " \n", 510 | " \n", 511 | " \n", 512 | " \n", 513 | " \n", 514 | " \n", 515 | " \n", 516 | " \n", 517 | " \n", 518 | " \n", 519 | " \n", 520 | " \n", 521 | " \n", 522 | " \n", 523 | " \n", 524 | " \n", 525 | " \n", 526 | " \n", 527 | " \n", 528 | " \n", 529 | " \n", 530 | " \n", 531 | " \n", 532 | " \n", 533 | " \n", 534 | " \n", 535 | " \n", 536 | " \n", 537 | " \n", 538 | " \n", 539 | " \n", 540 | " \n", 541 | " \n", 542 | " \n", 543 | " \n", 544 | " \n", 545 | " \n", 546 | " \n", 547 | " \n", 548 | " \n", 549 | "
statementsourcelinkveracity
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/0
12Says a photo shows a driver and passengers wearing moose heads in a truck with a man strapped to the roof that caused 16 accidents on I-35.Viral image/facebook-fact-checks/statements/2019/oct/24/viral-image/drunk-men-wearing-moose-heads-didnt-actually-terro/0
22AARP backed \"federal funding for Planned Parenthood.\"Association of Mature American Citizens/truth-o-meter/statements/2019/oct/22/association-mature-american-citizens/online-ads-claiming-aarp-backed-federal-funding-pl/0
32\"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\"Richard Ojeda/west-virginia/statements/2019/oct/17/richard-ojeda/how-many-americans-are-killed-and-injured-guns-eve/0
45Americans \"say that what they want is a choice\" to join a single-payer system like Medicare rather than ending private insurance.Pete Buttigieg/truth-o-meter/statements/2019/oct/16/pete-buttigieg/refereeing-pete-buttigieg-elizabeth-warren-medicar/1
56Says the whistleblower hired \"left-wing lawyers, left-wing firms, Soros involved in funding all of them.\"Mark Levin/punditfact/statements/2019/oct/11/mark-levin/fact-checking-claims-about-whistleblowers-legal-te/0
66\"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\"Donald Trump/truth-o-meter/statements/2019/oct/09/donald-trump/donald-trump-whistleblower-got-phone-call-almost-c/0
76\"50% of the DUIs on Interstate 35 are from illegals. Ninety percent of the 50% have absolutely no identification.\"Roger Williams/texas/statements/2019/oct/04/roger-williams/are-half-those-arrested-dwis-i-35-unauthorized-imm/0
87Says a photo shows Beto O’Rourke \"in college drunk and pissing his pants.\"Viral image/facebook-fact-checks/statements/2019/oct/02/viral-image/photo-philadelphia-musician-not-beto-orourke/0
98Says Republican Gov. Phil Scott \"just voted to impeach President Trump.\"Facebook posts/facebook-fact-checks/statements/2019/sep/30/facebook-posts/no-vermonts-governor-did-not-vote-impeach-donald-t/0
\n", 550 | "
" 551 | ], 552 | "text/plain": [ 553 | " statement \\\n", 554 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 555 | "12 Says a photo shows a driver and passengers wearing moose heads in a truck with a man strapped to the roof that caused 16 accidents on I-35. \n", 556 | "22 AARP backed \"federal funding for Planned Parenthood.\" \n", 557 | "32 \"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\" \n", 558 | "45 Americans \"say that what they want is a choice\" to join a single-payer system like Medicare rather than ending private insurance. \n", 559 | "56 Says the whistleblower hired \"left-wing lawyers, left-wing firms, Soros involved in funding all of them.\" \n", 560 | "66 \"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\" \n", 561 | "76 \"50% of the DUIs on Interstate 35 are from illegals. Ninety percent of the 50% have absolutely no identification.\" \n", 562 | "87 Says a photo shows Beto O’Rourke \"in college drunk and pissing his pants.\" \n", 563 | "98 Says Republican Gov. Phil Scott \"just voted to impeach President Trump.\" \n", 564 | "\n", 565 | " source \\\n", 566 | "0 Facebook posts \n", 567 | "12 Viral image \n", 568 | "22 Association of Mature American Citizens \n", 569 | "32 Richard Ojeda \n", 570 | "45 Pete Buttigieg \n", 571 | "56 Mark Levin \n", 572 | "66 Donald Trump \n", 573 | "76 Roger Williams \n", 574 | "87 Viral image \n", 575 | "98 Facebook posts \n", 576 | "\n", 577 | " link \\\n", 578 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 579 | "12 /facebook-fact-checks/statements/2019/oct/24/viral-image/drunk-men-wearing-moose-heads-didnt-actually-terro/ \n", 580 | "22 /truth-o-meter/statements/2019/oct/22/association-mature-american-citizens/online-ads-claiming-aarp-backed-federal-funding-pl/ \n", 581 | "32 /west-virginia/statements/2019/oct/17/richard-ojeda/how-many-americans-are-killed-and-injured-guns-eve/ \n", 582 | "45 /truth-o-meter/statements/2019/oct/16/pete-buttigieg/refereeing-pete-buttigieg-elizabeth-warren-medicar/ \n", 583 | "56 /punditfact/statements/2019/oct/11/mark-levin/fact-checking-claims-about-whistleblowers-legal-te/ \n", 584 | "66 /truth-o-meter/statements/2019/oct/09/donald-trump/donald-trump-whistleblower-got-phone-call-almost-c/ \n", 585 | "76 /texas/statements/2019/oct/04/roger-williams/are-half-those-arrested-dwis-i-35-unauthorized-imm/ \n", 586 | "87 /facebook-fact-checks/statements/2019/oct/02/viral-image/photo-philadelphia-musician-not-beto-orourke/ \n", 587 | "98 /facebook-fact-checks/statements/2019/sep/30/facebook-posts/no-vermonts-governor-did-not-vote-impeach-donald-t/ \n", 588 | "\n", 589 | " veracity \n", 590 | "0 0 \n", 591 | "12 0 \n", 592 | "22 0 \n", 593 | "32 0 \n", 594 | "45 1 \n", 595 | "56 0 \n", 596 | "66 0 \n", 597 | "76 0 \n", 598 | "87 0 \n", 599 | "98 0 " 600 | ] 601 | }, 602 | "execution_count": 10, 603 | "metadata": {}, 604 | "output_type": "execute_result" 605 | } 606 | ], 607 | "source": [ 608 | "# randomly sample 10 rows\n", 609 | "ver_df.iloc[0:100:10]" 610 | ] 611 | }, 612 | { 613 | "cell_type": "code", 614 | "execution_count": 11, 615 | "metadata": {}, 616 | "outputs": [ 617 | { 618 | "data": { 619 | "text/html": [ 620 | "
\n", 621 | "\n", 634 | "\n", 635 | " \n", 636 | " \n", 637 | " \n", 638 | " \n", 639 | " \n", 640 | " \n", 641 | " \n", 642 | " \n", 643 | " \n", 644 | " \n", 645 | " \n", 646 | " \n", 647 | " \n", 648 | " \n", 649 | " \n", 650 | " \n", 651 | " \n", 652 | " \n", 653 | " \n", 654 | " \n", 655 | " \n", 656 | " \n", 657 | " \n", 658 | " \n", 659 | " \n", 660 | " \n", 661 | " \n", 662 | " \n", 663 | " \n", 664 | " \n", 665 | " \n", 666 | " \n", 667 | " \n", 668 | " \n", 669 | " \n", 670 | " \n", 671 | " \n", 672 | " \n", 673 | " \n", 674 | " \n", 675 | " \n", 676 | " \n", 677 | " \n", 678 | " \n", 679 | " \n", 680 | " \n", 681 | " \n", 682 | " \n", 683 | " \n", 684 | " \n", 685 | " \n", 686 | " \n", 687 | " \n", 688 | " \n", 689 | " \n", 690 | " \n", 691 | " \n", 692 | " \n", 693 | " \n", 694 | " \n", 695 | " \n", 696 | " \n", 697 | " \n", 698 | " \n", 699 | " \n", 700 | " \n", 701 | " \n", 702 | " \n", 703 | " \n", 704 | " \n", 705 | " \n", 706 | " \n", 707 | " \n", 708 | " \n", 709 | " \n", 710 | " \n", 711 | " \n", 712 | " \n", 713 | " \n", 714 | " \n", 715 | " \n", 716 | " \n", 717 | " \n", 718 | " \n", 719 | " \n", 720 | " \n", 721 | " \n", 722 | " \n", 723 | "
statementsourcelinkveracity
count13197131971319713197.000000
unique13191358513197NaN
topSays Mitt Romney flip-flopped on abortion.Donald Trump/truth-o-meter/statements/2008/apr/09/hillary-clinton/he-had-it-wrapped-up-in-march/NaN
freq26251NaN
meanNaNNaNNaN0.405395
stdNaNNaNNaN0.490987
minNaNNaNNaN0.000000
25%NaNNaNNaN0.000000
50%NaNNaNNaN0.000000
75%NaNNaNNaN1.000000
maxNaNNaNNaN1.000000
\n", 724 | "
" 725 | ], 726 | "text/plain": [ 727 | " statement source \\\n", 728 | "count 13197 13197 \n", 729 | "unique 13191 3585 \n", 730 | "top Says Mitt Romney flip-flopped on abortion. Donald Trump \n", 731 | "freq 2 625 \n", 732 | "mean NaN NaN \n", 733 | "std NaN NaN \n", 734 | "min NaN NaN \n", 735 | "25% NaN NaN \n", 736 | "50% NaN NaN \n", 737 | "75% NaN NaN \n", 738 | "max NaN NaN \n", 739 | "\n", 740 | " link \\\n", 741 | "count 13197 \n", 742 | "unique 13197 \n", 743 | "top /truth-o-meter/statements/2008/apr/09/hillary-clinton/he-had-it-wrapped-up-in-march/ \n", 744 | "freq 1 \n", 745 | "mean NaN \n", 746 | "std NaN \n", 747 | "min NaN \n", 748 | "25% NaN \n", 749 | "50% NaN \n", 750 | "75% NaN \n", 751 | "max NaN \n", 752 | "\n", 753 | " veracity \n", 754 | "count 13197.000000 \n", 755 | "unique NaN \n", 756 | "top NaN \n", 757 | "freq NaN \n", 758 | "mean 0.405395 \n", 759 | "std 0.490987 \n", 760 | "min 0.000000 \n", 761 | "25% 0.000000 \n", 762 | "50% 0.000000 \n", 763 | "75% 1.000000 \n", 764 | "max 1.000000 " 765 | ] 766 | }, 767 | "execution_count": 11, 768 | "metadata": {}, 769 | "output_type": "execute_result" 770 | } 771 | ], 772 | "source": [ 773 | "# how many unique items per category?\n", 774 | "ver_df.describe(include='all')" 775 | ] 776 | }, 777 | { 778 | "cell_type": "code", 779 | "execution_count": 12, 780 | "metadata": {}, 781 | "outputs": [ 782 | { 783 | "data": { 784 | "text/plain": [ 785 | "Donald Trump 625\n", 786 | "Bloggers 463\n", 787 | "Barack Obama 439\n", 788 | "Facebook posts 250\n", 789 | "Viral image 233\n", 790 | "Hillary Clinton 229\n", 791 | "Chain email 173\n", 792 | "Scott Walker 162\n", 793 | "John McCain 153\n", 794 | "Mitt Romney 148\n", 795 | "Name: source, dtype: int64" 796 | ] 797 | }, 798 | "execution_count": 12, 799 | "metadata": {}, 800 | "output_type": "execute_result" 801 | } 802 | ], 803 | "source": [ 804 | "# top 10 sources\n", 805 | "ver_df.source.value_counts()[:10]" 806 | ] 807 | }, 808 | { 809 | "cell_type": "markdown", 810 | "metadata": {}, 811 | "source": [ 812 | "# Verify the dates of the data" 813 | ] 814 | }, 815 | { 816 | "cell_type": "code", 817 | "execution_count": 13, 818 | "metadata": {}, 819 | "outputs": [], 820 | "source": [ 821 | "# extracting the date from the link column\n", 822 | "# r() = first group to extract; you can use multiple ()\n", 823 | "# ?P = column name for convenience\n", 824 | "# \\d = digit\n", 825 | "# {n} = number of digits to include\n", 826 | "# . = wildcard\n", 827 | "# + = greedy search\n", 828 | "# ? = but not too greedy\n", 829 | "ver_df[\"date\"] = ver_df.link.str.extract(r'(\\d{4}/.+?\\d{2})')" 830 | ] 831 | }, 832 | { 833 | "cell_type": "code", 834 | "execution_count": 14, 835 | "metadata": {}, 836 | "outputs": [ 837 | { 838 | "data": { 839 | "text/html": [ 840 | "
\n", 841 | "\n", 854 | "\n", 855 | " \n", 856 | " \n", 857 | " \n", 858 | " \n", 859 | " \n", 860 | " \n", 861 | " \n", 862 | " \n", 863 | " \n", 864 | " \n", 865 | " \n", 866 | " \n", 867 | " \n", 868 | " \n", 869 | " \n", 870 | " \n", 871 | " \n", 872 | " \n", 873 | " \n", 874 | " \n", 875 | " \n", 876 | " \n", 877 | " \n", 878 | " \n", 879 | " \n", 880 | " \n", 881 | " \n", 882 | " \n", 883 | " \n", 884 | " \n", 885 | " \n", 886 | " \n", 887 | " \n", 888 | " \n", 889 | " \n", 890 | " \n", 891 | "
statementsourcelinkveracitydate
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/02019/oct/25
1Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\"Viral image/facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/02019/oct/25
3\"14,000 abandoned wind turbines litter the United States.\"Chain email/missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/02019/oct/25
\n", 892 | "
" 893 | ], 894 | "text/plain": [ 895 | " statement \\\n", 896 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 897 | "1 Says Ann Landers said, \"At age 20, we worry about what others think of us. At age 40, we don’t care what they think. At age 60, we discover that they have not been thinking of us at all.\" \n", 898 | "3 \"14,000 abandoned wind turbines litter the United States.\" \n", 899 | "\n", 900 | " source \\\n", 901 | "0 Facebook posts \n", 902 | "1 Viral image \n", 903 | "3 Chain email \n", 904 | "\n", 905 | " link \\\n", 906 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 907 | "1 /facebook-fact-checks/statements/2019/oct/25/viral-image/no-evidence-ann-landers-said-quote-about-age/ \n", 908 | "3 /missouri/statements/2019/oct/25/chain-email/no-there-arent-14000-abandoned-wind-turbines-litte/ \n", 909 | "\n", 910 | " veracity date \n", 911 | "0 0 2019/oct/25 \n", 912 | "1 0 2019/oct/25 \n", 913 | "3 0 2019/oct/25 " 914 | ] 915 | }, 916 | "execution_count": 14, 917 | "metadata": {}, 918 | "output_type": "execute_result" 919 | } 920 | ], 921 | "source": [ 922 | "ver_df.head(3)" 923 | ] 924 | }, 925 | { 926 | "cell_type": "code", 927 | "execution_count": 15, 928 | "metadata": {}, 929 | "outputs": [], 930 | "source": [ 931 | "# change the date column to a datetime column for convenience\n", 932 | "ver_df.date = pd.to_datetime(ver_df.date,infer_datetime_format=True)" 933 | ] 934 | }, 935 | { 936 | "cell_type": "code", 937 | "execution_count": 16, 938 | "metadata": {}, 939 | "outputs": [ 940 | { 941 | "name": "stdout", 942 | "output_type": "stream", 943 | "text": [ 944 | "\n", 945 | "Int64Index: 13197 entries, 0 to 16610\n", 946 | "Data columns (total 5 columns):\n", 947 | " # Column Non-Null Count Dtype \n", 948 | "--- ------ -------------- ----- \n", 949 | " 0 statement 13197 non-null object \n", 950 | " 1 source 13197 non-null object \n", 951 | " 2 link 13197 non-null object \n", 952 | " 3 veracity 13197 non-null int64 \n", 953 | " 4 date 13197 non-null datetime64[ns]\n", 954 | "dtypes: datetime64[ns](1), int64(1), object(3)\n", 955 | "memory usage: 618.6+ KB\n" 956 | ] 957 | } 958 | ], 959 | "source": [ 960 | "ver_df.info()" 961 | ] 962 | }, 963 | { 964 | "cell_type": "code", 965 | "execution_count": 17, 966 | "metadata": {}, 967 | "outputs": [ 968 | { 969 | "data": { 970 | "text/html": [ 971 | "
\n", 972 | "\n", 985 | "\n", 986 | " \n", 987 | " \n", 988 | " \n", 989 | " \n", 990 | " \n", 991 | " \n", 992 | " \n", 993 | " \n", 994 | " \n", 995 | " \n", 996 | " \n", 997 | " \n", 998 | " \n", 999 | " \n", 1000 | " \n", 1001 | " \n", 1002 | " \n", 1003 | " \n", 1004 | " \n", 1005 | " \n", 1006 | " \n", 1007 | " \n", 1008 | " \n", 1009 | " \n", 1010 | " \n", 1011 | " \n", 1012 | " \n", 1013 | " \n", 1014 | " \n", 1015 | " \n", 1016 | " \n", 1017 | " \n", 1018 | " \n", 1019 | " \n", 1020 | " \n", 1021 | " \n", 1022 | "
statementsourcelinkveracitydate
0Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"Facebook posts/facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/02019-10-25
32\"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\"Richard Ojeda/west-virginia/statements/2019/oct/17/richard-ojeda/how-many-americans-are-killed-and-injured-guns-eve/02019-10-17
66\"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\"Donald Trump/truth-o-meter/statements/2019/oct/09/donald-trump/donald-trump-whistleblower-got-phone-call-almost-c/02019-10-09
\n", 1023 | "
" 1024 | ], 1025 | "text/plain": [ 1026 | " statement \\\n", 1027 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 1028 | "32 \"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\" \n", 1029 | "66 \"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\" \n", 1030 | "\n", 1031 | " source \\\n", 1032 | "0 Facebook posts \n", 1033 | "32 Richard Ojeda \n", 1034 | "66 Donald Trump \n", 1035 | "\n", 1036 | " link \\\n", 1037 | "0 /facebook-fact-checks/statements/2019/oct/25/facebook-posts/no-british-parliament-didnt-ban-witchcraft-lipstic/ \n", 1038 | "32 /west-virginia/statements/2019/oct/17/richard-ojeda/how-many-americans-are-killed-and-injured-guns-eve/ \n", 1039 | "66 /truth-o-meter/statements/2019/oct/09/donald-trump/donald-trump-whistleblower-got-phone-call-almost-c/ \n", 1040 | "\n", 1041 | " veracity date \n", 1042 | "0 0 2019-10-25 \n", 1043 | "32 0 2019-10-17 \n", 1044 | "66 0 2019-10-09 " 1045 | ] 1046 | }, 1047 | "execution_count": 17, 1048 | "metadata": {}, 1049 | "output_type": "execute_result" 1050 | } 1051 | ], 1052 | "source": [ 1053 | "ver_df[:90:30]" 1054 | ] 1055 | }, 1056 | { 1057 | "cell_type": "code", 1058 | "execution_count": 18, 1059 | "metadata": {}, 1060 | "outputs": [ 1061 | { 1062 | "data": { 1063 | "image/png": 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\n", 1064 | "text/plain": [ 1065 | "
" 1066 | ] 1067 | }, 1068 | "metadata": { 1069 | "needs_background": "light" 1070 | }, 1071 | "output_type": "display_data" 1072 | } 1073 | ], 1074 | "source": [ 1075 | "#by year\n", 1076 | "ax = ver_df.groupby(ver_df.date.dt.year).count().plot(kind=\"bar\")\n", 1077 | "ax.legend_ = None\n", 1078 | "plt.title(\"Distribution by Year\")\n", 1079 | "plt.show()" 1080 | ] 1081 | }, 1082 | { 1083 | "cell_type": "code", 1084 | "execution_count": 19, 1085 | "metadata": {}, 1086 | "outputs": [ 1087 | { 1088 | "data": { 1089 | "image/png": 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\n", 1090 | "text/plain": [ 1091 | "
" 1092 | ] 1093 | }, 1094 | "metadata": { 1095 | "needs_background": "light" 1096 | }, 1097 | "output_type": "display_data" 1098 | } 1099 | ], 1100 | "source": [ 1101 | "#by month\n", 1102 | "ax = ver_df.groupby(ver_df.date.dt.month).count().plot(kind=\"bar\")\n", 1103 | "ax.legend_ = None\n", 1104 | "plt.title(\"Distribution by Month\")\n", 1105 | "plt.show()" 1106 | ] 1107 | }, 1108 | { 1109 | "cell_type": "code", 1110 | "execution_count": 20, 1111 | "metadata": {}, 1112 | "outputs": [], 1113 | "source": [ 1114 | "cleaned_df = ver_df[[\"date\",\"source\",\"statement\",\"veracity\"]]" 1115 | ] 1116 | }, 1117 | { 1118 | "cell_type": "code", 1119 | "execution_count": 21, 1120 | "metadata": { 1121 | "scrolled": false 1122 | }, 1123 | "outputs": [ 1124 | { 1125 | "data": { 1126 | "text/html": [ 1127 | "
\n", 1128 | "\n", 1141 | "\n", 1142 | " \n", 1143 | " \n", 1144 | " \n", 1145 | " \n", 1146 | " \n", 1147 | " \n", 1148 | " \n", 1149 | " \n", 1150 | " \n", 1151 | " \n", 1152 | " \n", 1153 | " \n", 1154 | " \n", 1155 | " \n", 1156 | " \n", 1157 | " \n", 1158 | " \n", 1159 | " \n", 1160 | " \n", 1161 | " \n", 1162 | " \n", 1163 | " \n", 1164 | " \n", 1165 | " \n", 1166 | " \n", 1167 | " \n", 1168 | " \n", 1169 | " \n", 1170 | " \n", 1171 | " \n", 1172 | " \n", 1173 | " \n", 1174 | " \n", 1175 | " \n", 1176 | " \n", 1177 | " \n", 1178 | " \n", 1179 | " \n", 1180 | " \n", 1181 | " \n", 1182 | " \n", 1183 | " \n", 1184 | " \n", 1185 | " \n", 1186 | " \n", 1187 | " \n", 1188 | " \n", 1189 | " \n", 1190 | " \n", 1191 | " \n", 1192 | " \n", 1193 | " \n", 1194 | " \n", 1195 | " \n", 1196 | " \n", 1197 | " \n", 1198 | " \n", 1199 | " \n", 1200 | " \n", 1201 | " \n", 1202 | " \n", 1203 | " \n", 1204 | " \n", 1205 | " \n", 1206 | " \n", 1207 | " \n", 1208 | " \n", 1209 | " \n", 1210 | " \n", 1211 | " \n", 1212 | " \n", 1213 | " \n", 1214 | " \n", 1215 | " \n", 1216 | " \n", 1217 | " \n", 1218 | " \n", 1219 | " \n", 1220 | " \n", 1221 | " \n", 1222 | " \n", 1223 | "
datesourcestatementveracity
02019-10-25Facebook postsSays that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\"0
122019-10-24Viral imageSays a photo shows a driver and passengers wearing moose heads in a truck with a man strapped to the roof that caused 16 accidents on I-35.0
222019-10-22Association of Mature American CitizensAARP backed \"federal funding for Planned Parenthood.\"0
322019-10-17Richard Ojeda\"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\"0
452019-10-16Pete ButtigiegAmericans \"say that what they want is a choice\" to join a single-payer system like Medicare rather than ending private insurance.1
562019-10-11Mark LevinSays the whistleblower hired \"left-wing lawyers, left-wing firms, Soros involved in funding all of them.\"0
662019-10-09Donald Trump\"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\"0
762019-10-04Roger Williams\"50% of the DUIs on Interstate 35 are from illegals. Ninety percent of the 50% have absolutely no identification.\"0
872019-10-02Viral imageSays a photo shows Beto O’Rourke \"in college drunk and pissing his pants.\"0
982019-09-30Facebook postsSays Republican Gov. Phil Scott \"just voted to impeach President Trump.\"0
\n", 1224 | "
" 1225 | ], 1226 | "text/plain": [ 1227 | " date source \\\n", 1228 | "0 2019-10-25 Facebook posts \n", 1229 | "12 2019-10-24 Viral image \n", 1230 | "22 2019-10-22 Association of Mature American Citizens \n", 1231 | "32 2019-10-17 Richard Ojeda \n", 1232 | "45 2019-10-16 Pete Buttigieg \n", 1233 | "56 2019-10-11 Mark Levin \n", 1234 | "66 2019-10-09 Donald Trump \n", 1235 | "76 2019-10-04 Roger Williams \n", 1236 | "87 2019-10-02 Viral image \n", 1237 | "98 2019-09-30 Facebook posts \n", 1238 | "\n", 1239 | " statement \\\n", 1240 | "0 Says that in 1770 \"British parliament banned lipstick, saying it had the power to seduce men into marriage, which was classified as witchcraft.\" \n", 1241 | "12 Says a photo shows a driver and passengers wearing moose heads in a truck with a man strapped to the roof that caused 16 accidents on I-35. \n", 1242 | "22 AARP backed \"federal funding for Planned Parenthood.\" \n", 1243 | "32 \"75-100 folks (are) killed a month and over 200 wounded by senseless gun violence.\" \n", 1244 | "45 Americans \"say that what they want is a choice\" to join a single-payer system like Medicare rather than ending private insurance. \n", 1245 | "56 Says the whistleblower hired \"left-wing lawyers, left-wing firms, Soros involved in funding all of them.\" \n", 1246 | "66 \"The first so-called second hand information ‘Whistleblower’ got my phone conversation almost completely wrong.\" \n", 1247 | "76 \"50% of the DUIs on Interstate 35 are from illegals. Ninety percent of the 50% have absolutely no identification.\" \n", 1248 | "87 Says a photo shows Beto O’Rourke \"in college drunk and pissing his pants.\" \n", 1249 | "98 Says Republican Gov. Phil Scott \"just voted to impeach President Trump.\" \n", 1250 | "\n", 1251 | " veracity \n", 1252 | "0 0 \n", 1253 | "12 0 \n", 1254 | "22 0 \n", 1255 | "32 0 \n", 1256 | "45 1 \n", 1257 | "56 0 \n", 1258 | "66 0 \n", 1259 | "76 0 \n", 1260 | "87 0 \n", 1261 | "98 0 " 1262 | ] 1263 | }, 1264 | "execution_count": 21, 1265 | "metadata": {}, 1266 | "output_type": "execute_result" 1267 | } 1268 | ], 1269 | "source": [ 1270 | "cleaned_df[:100:10]" 1271 | ] 1272 | }, 1273 | { 1274 | "cell_type": "code", 1275 | "execution_count": 22, 1276 | "metadata": {}, 1277 | "outputs": [], 1278 | "source": [ 1279 | "cleaned_df.to_csv('2020_04_13_politifact_cleaned_data.csv')" 1280 | ] 1281 | } 1282 | ], 1283 | "metadata": { 1284 | "kernelspec": { 1285 | "display_name": "Python 3", 1286 | "language": "python", 1287 | "name": "python3" 1288 | }, 1289 | "language_info": { 1290 | "codemirror_mode": { 1291 | "name": "ipython", 1292 | "version": 3 1293 | }, 1294 | "file_extension": ".py", 1295 | "mimetype": "text/x-python", 1296 | "name": "python", 1297 | "nbconvert_exporter": "python", 1298 | "pygments_lexer": "ipython3", 1299 | "version": "3.7.6" 1300 | } 1301 | }, 1302 | "nbformat": 4, 1303 | "nbformat_minor": 2 1304 | } 1305 | --------------------------------------------------------------------------------