An open-source, community oversight dataset of all U.S. Prosecutors. Happy Hacktoberfest 🎃

🇺🇸🏁 Draw a beautiful county-level election results map with only a few lines of code

Website that allows you to see what the outcome of the US elections could have been if different seat allocation algorithms were used.

Predicting US Presidential Election 2020 Result Using Twitter Sentiment Analysis with Python.

Predicting election results by county for the 2016 US general election with machine learning in R.

Visualization project based on FEC records with a particular focus on candidate donor overlap and mapping donors to zipcode demographics.

fake bot detection, evolution of bots, cluster analysis, US election twitter data, social media mining, influence of twitter bots on 2016 US election

What happened in the 2016 US Elections? What kind of population in the United States voted for Democrats and Republicans?

Pollsters poll the public, Impostor polls the pollsters

Political observatory for US 2020 election using twitter data.

This repository includes code for a predictive model I created which classifies counties that Trump won and a data exploration tool that plots the Trump county score along with a number of demographic variables over a county-level map of the US.

Analysis twitter network of 2016 US troll account using degree, centrality, betweenness, modularity, etc.

An app that returns the address for the SOE office when given a zip-code.

Python Visualization notebook using data from US Election 2020 Tweets ·

Modelling and forecasting US election outcomes 🗽 ELT in python 🐍 OLS in Stata 🔢

Exploratory Data Analysis of contributions from Texas for 2016 US presidential election data. Udacity EDA course project.

So You’re Planning to Vote In Fascist America

Code for collecting and cleaning speeches (text) of the US 2020 election campaign. Corresponding publication: "A text dataset of campaign speeches of the main tickets in the 2020 US presidential election", by Ioannis Chalkiadakis, Louise Anglès d’Auriac, Gareth W. Peters, and Divina Frau-Meigs