A Reddit (r/greatawakening ban intervention, 2018) dataset of 329,183 pre-ban posts from banned community, 690,552 pre-ban control posts, 620,307 post-ban control posts, collected by Cerulli et al. via Reddit API (ICWSM 2026). Each record contains comment ID, selftext (post body), author (pseudonymized), subreddit, score, created_utc, split label (in-before/out-before/out-after). TBBT r/greatawakening: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A MADOC (Reddit, greatawakening) dataset of 18,267 users and 302,678 reply edges from 915,265 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
