4 datasets tagged as the tag “Us congress”.
4 datasets.
A Facebook Congress dataset of 548,341 posts, 13,866,507 responses, collected by Peixian and Zhang. Each record contains posts, responses, op_gender, responder_gender, sentiment, relevance. rtGender dataset for Facebook Congress — studies gendered responses in online discourse. Suitable for gender studies, sentiment analysis, response prediction.
A Twitter dataset of 5,072,124 tweets from 1,835 congressional accounts, collected by Alex Litel via Twitter API (2017-2023). Each record contains tweet text, screen name, user ID, timestamp, retweet count, favorite count, source, retweet status. A daily collection of tweets from U.S. Congress members, committees, caucuses and party accounts, one JSON file per day; 11 days have no file in the source repository (for example 2022-01-15, 2022-03-17 and 2022-10-24 to 2022-10-31). metadata/historical-users-filtered.json, from the collection's companion repository, maps each account to its member or office, chamber, party and type. Suitable for political communication, sentiment analysis, election studies, congressional behavior, social media analysis.
A twitter dataset of 2,041,399 tweet IDs from all members of the 115th U.S. Congress, collected by Littman via Social Feed Manager (GWU Libraries). Each record contains tweet IDs only — full content requires hydration. Complete tweet archive from all 115th Congress members enabling legislator communication and retweet network analysis. Suitable for political discourse, legislator communication patterns, congressional social media behavior.
A NDS-VU signed network repository dataset of 220 Congress members and 521 signed co-sponsorship edges, collected by NDS-VU (Vrije Universiteit Amsterdam). Each record contains directed signed edges between nodes: sign (+1 or -1) representing positive/negative relationships; no edge weights beyond binary sign. Signed network of U.S. Congress members based on bill co-sponsorship patterns, where positive edges indicate co-sponsorship and negative edges indicate opposition, enabling political alignment and polarization analysis. Suitable for political polarization, signed network analysis, legislative behavior.
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