jpfairbanks/newsgraphing

Code for analyzing Fake News

News Graphing

This repository contains code for studying the network of fake news, including code and data for JF, NF, NK, and EB "Credibility in the News: Do we need to read?" WSDM 2018 workshop on Misinformation and Misbehavior online, http://jpfairbanks.com/mis2-2018.

This codebase includes both a python package and a collection of julia scripts for analyzing fake news. We use NLP tools in python including the fabulous SpaCy library, and classifiers in sklearn. The Belief Propagation that appears here is written in Julia using LightGraphs.jl graphs.

We use PostgreSQL and MongoDB to store structured and unstructured data regarding the articles. For the purpose of reproducibility a static snapshot of the data has been made available through the src/newgraphing/download.py script. In our live system this analysis can be conducted against the data as it is updated every 15 minutes.

Getting Started

Here are some instructions to get going with this project

Depedencies

• julia
• python, pip
• git-lfs

Installing

1. Download the code git clone github.com/jpfairbanks/newsgraphing && cd newsgraphing
2. Install all dependencies with pip install .
3. Install all julia dependencies in the src/fakeprop/REQUIRE file with Pkg.add
4. Run the main script to generate figures python ./main.py

Contributing

If anything is unclear or doesn't work, let us know on the issues page. Feel free to ask for help by opening a new issue and we will take a look and answer your questions.

Contributors

• James Fairbanks
• Nate Knauf
• Natalie Fitch
• David Ediger
• Erica Briscoe