polarisation, echo chambers
9 datasets tagged as the topic “Polarization”.
9 datasets.
A twitter dataset of 295,670,111 tweet IDs from the 2020 U.S. presidential election, collected by Wrubel and Kerchner via Social Feed Manager (GWU Libraries). Each record contains tweet IDs only — full content requires hydration. Complete tweet archive from the 2020 election including post-election period and January 6 lead-up. Suitable for election discourse, misinformation, political polarization, post-election unrest.
A twitter dataset of 767,139 tweet IDs from #BlackLivesMatter and #AllLivesMatter (10% Gardenhose sample, Aug 2014–Aug 2015), collected by Gallagher (Northeastern University, 2018). Each record contains tweet IDs only — full content requires hydration. Paired collection of #BLM and #ALM tweets enabling contrastive social movement analysis. Suitable for social movement analysis, racial discourse, political polarization.
A Twitter dataset of 128,484 tweets with political leaning labels, collected by Chatelet via Hugging Face. Each record contains text, political label (liberal, conservative, neutral). 100K tweets labeled for political ideology with balanced classes. Suitable for political NLP, ideology classification, discourse analysis.
A Reddit dataset of 54,075 subreddits and 571,927 directed hyperlinks (510,787 positive sentiment, 61,140 negative sentiment) from post hyperlinks embedded in post titles, collected by Kumar et al. via Reddit API, January 2014 to April 2017, distributed by SNAP. Each record contains directed edges from source to target subreddit with binary sentiment label (+1/-1) and 86-dimension text property vector; post ID and timestamp per edge. captures cross-community interaction and conflict on Reddit with sentiment polarity per hyperlink, enabling study of how communities reference each other positively vs. antagonistically over time. Suitable for community conflict detection, cross-community interaction modeling, signed network analysis, temporal network analysis, and online community dynamics research.
A Twitter dataset of 18470 nodes, 48365 edges, collected by Nikolov et al. (OSoMe/Indiana University), 2010. Each record contains retweet edgelist, mention edgelist, node political labels (left/right/-). Twitter retweet and mention networks from 2010 with political leaning labels per user; three graph types for polarization analysis.. Suitable for Political polarization, echo chamber detection, social bubble measurement..
A NDS-VU signed network repository dataset of 10,885 users and 251,406 signed interaction edges from Italian referendum Twitter, collected by NDS-VU (Vrije Universiteit Amsterdam, 2016). Each record contains directed signed edges between nodes: sign (+1 or -1) representing positive/negative relationships; no edge weights beyond binary sign. Signed retweet/mention network from the 2016 Italian constitutional referendum on Twitter, where edges represent support (+1) or opposition (-1) interactions between users discussing the referendum. Suitable for political polarization, signed social network analysis, referendum discourse.
A Reddit dataset of 5,024 annotated comments, 809,713 total comments, collected by Behavioral Data Science Lab. Each record contains comment text, stance labels, interaction graphs, polarity scores. r/Brexit subreddit with crowd-annotated stance labels and temporal interaction graphs. Suitable for political polarization, opinion dynamics, stance detection.
A Political blogosphere (US 2004 election) dataset of 1,224 nodes and 19,025 edges, collected by Adamic & Glance via blog crawl. Each record contains directed edges: True, weighted: False, signed: False. This directed network contains front-page hyperlinks between blogs in the context of the 2004 US election. A node represents a blog and an edge represents a hyperlink between two blogs.. Suitable for political polarization, community detection, information diffusion.
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.
Twitter (X)
Reddit