Ben Horne's repositories
fakenewsdata1
This repository contains two independent news datasets used in the 2017 study: "This Just In: Fake News Packs a Lot in Title, Uses Simpler, Repetitive Content in Text Body, More Similar to Satire than Real News"
The-NELA-Toolkit
The News Landscape Toolkit (NELA)
Language-Features-for-News
Language features used in the NELA Toolkit and other news studies
NELAFeatures
NELA Features for News Veracity. Used in multiple studies.
Reddit_Community_Scraper
General Subreddit Scraper
Stochastic-Kronecker-Generator
Stochastic Kronecker Generation in Python, Used in RPI TRUST
NewsNetworks
Code to generate content sharing networks of news sources, as used in ICWSM 2019 study. This code is specifically built to run on a NELA-GT database, but can easily be modified for other data sources.
reddit-scraped-worldnews-dataset
News articles scraped from posts during 2012 and 2013 in the popular news community on reddit: r/worldnews.
archive_news_cc
Closed Caption Transcripts of News Videos from archive.org + Scripts for Downloading and Parsing the data
LocalNewsDataset
The documentation and scripts for the Local News Dataset
Open-Source-Basketball-Heat-Map-Maker
This program was used in the paper "From Sports to Science: Using Basketball Analytics to Broaden the Appeal of Math and Science Among Youth" published at MIT Sports Analytics Conference 2017
QuickKetchup
Automated method for testing strategies in Draft Day Sports: Pro Football 2016. Primary used in the ISFL (http://forum.sim-football.com/).
2017-08-partisan-sites-and-facebook-pages
Data, analytic code, and findings related to the BuzzFeed News article, "Inside The Partisan Fight For Your News Feed," published August 8, 2017.
Fast_CSV_Combiner
CSV combiner Python
politeness
Sample implementation of a politeness model, trained on the Stanford Politeness Corpus
Simple_Language_Feature_Tools
A set of simple language features for plain text files
the-algorithm
Source code for Twitter's Recommendation Algorithm
youtube_channel_mining
Mining summary data from a YouTube channel