A MADOC (Reddit, KotakuInAction) dataset of 83,581 users and 1,758,653 reply edges from 6,793,795 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.
A Scored.co (c/KotakuInAction2) dataset of 39,318 submissions and 707,897 comments from 1,757 unique authors in c/KotakuInAction2 (2020-2023), collected by iDRAMA Lab via Scored.co API (2024). Each record contains post/comment text, author, score up/down, NSFW/deleted/twitter-crosspost flags, date, UUID. c/KotakuInAction2 on Scored.co — Gaming culture commentary, migrated from Reddit r/KotakuInAction. 747,215 total posts from 1,757 authors over 4 years. Suitable for deplatforming research, community behavior analysis, alternative platform discourse, content moderation effects, longitudinal community evolution.
A Voat (Reddit alternative, 2013–2020) dataset of 2,821 submissions, 17,053 comments, 4,135 users, 10,917 collaboration edges, collected by Mekacher & Papasavva (ICWSM 2022) via full platform crawl. Each record contains user nodes (registration date, moderation status), directed weighted edges (commenter→submitter, weight=upvotes+1), submission titles and bodies, comment text, upvotes, downvotes, depth. Complete dataset for the Voat subverse v/KotakuInAction, covering its full lifetime on the platform (2013–2020). Includes all 2,821 submissions and 17,053 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A MADOC (Voat, KotakuInAction) dataset of 1,878 users and 3,854 reply edges from 7,853 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.
Reddit
Scored
Voat