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Congressional Articles Mining

Project Overview

This project employs data mining and machine learning techniques to analyze textual data produced by U.S. Congress members, offering insights into political communication trends. By collecting a comprehensive dataset of articles and statements from various U.S. Congressmen and Congresswomen, we aim to explore key political patterns and their underlying motivations.

Data

A list of all United States Representatives was compiled from the official House website: Directory of Representatives (https://www.house.gov/). This data includes each representative’s full name, district, state, committee assignments, party affiliation, and a link to their individual webpage. Many of these individual webpages contain a dedicated ”Issues” subpage where representatives outline the topics they address in their published articles.

Articles per issue

Topics

Keyphrases over time

Keyphrase occurence

How to run

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

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