Analysis of fake news sites and viral posts, 2016 vs. 2017
This repository contains data and analysis supporting the BuzzFeed News article, "These Are 50 Of The Biggest Fake News Hits On Facebook In 2017", published Thursday, December 28, 2017. Please read that article, which contains important context and methodological details, before proceeding.
The data in this repository was compiled by BuzzFeed News using BuzzSumo, our own data collection, and this PolitiFact list. For additional details, please see the main BuzzFeed News article referenced above.
fact_check.csv: Titles and URLs of the top 50 fake news articles of 2017 along with associated fact-checking articles and their engagement numbers
sites_2016.csv: All URLs in our 2016 collection of sites that regularly publish completely fabricated articles
sites_2017.csv: All URLs in our 2017 collection of sites that regularly publish completely fabricated articles
top_2016.csv: The top 50 fake news articles of 2016 (by Facebook engagement) published by our 2016 list of fake news sites
top_2017.csv: The top 50 fake news articles of 2017 (by Facebook engagement) published by our 2017 list of fake news sites
The analysis is contained within this notebook. The Python code in that notebook also produces one output file. This file,
output/top_domains_comparison.csv, compares the count of unique domains from the list of top 50 fake news articles in 2016 with the equivalent list from 2017.
To reproduce the calculations and produce the output file, you will need to do the following:
- Ensure that you have installed Python and the Python libraries listed in
jupyter notebookfrom either the root or the
notebooks/fake-news-analysis.ipynbin Jupyter and run all the notebook’s cells.
Note: The Makefile and cleaning scripts are contained for reference but are not necessary to reproduce this analysis.
Contact Scott Pham at email@example.com.
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