A MADOC (Reddit, gaming) dataset of 2,870,130 users and 14,950,380 reply edges from 44,274,130 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 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 Stack Exchange (gaming.stackexchange.com) dataset of 64,732 users, 130,646 answer-collaboration edges, 100,896 questions, 163,928 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from gaming.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Stack Exchange (rpg.stackexchange.com) dataset of 20,080 users, 84,738 answer-collaboration edges, 49,580 questions, 111,678 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from rpg.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Stack Exchange (gamedev.stackexchange.com) dataset of 29,965 users, 65,238 answer-collaboration edges, 56,729 questions, 81,514 answers, collected by Stack Exchange, Inc. via the annual Stack Exchange Data Dump. Each record contains user nodes (reputation, badge counts, vote history), directed weighted edges (answerer→asker, weight=answer score, count=interactions, accepted=bool), post text, tag distribution. User collaboration network from gamedev.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Scored.co (c/Gaming) dataset of 10,679 submissions and 170,790 comments from 1,545 unique authors in c/Gaming (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/Gaming on Scored.co — Video game discussion community. 181,469 total posts from 1,545 authors over 4 years. Suitable for deplatforming research, community behavior analysis, alternative platform discourse, content moderation effects, longitudinal community evolution.
A Twitch (gaming social network) dataset of 168,116 users and 6,797,558 mutual follower edges, collected by Rozemberczki & Sarkar via Twitch public API (2018). Each record contains undirected mutual follower edges, node features (views, mature, life_time, created_at, updated_at, dead_account, language, affiliate). The dataset is notable for its large-scale strongly connected component with no missing attributes, designed for node classification and count data regression. Intended for research into social network analysis, node classification, community detection, and transfer learning in gaming communities.
A Voat (Reddit alternative, 2013–2020) dataset of 25,571 submissions, 144,180 comments, 24,579 users, 85,476 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/gaming, covering its full lifetime on the platform (2013–2020). Includes all 25,571 submissions and 144,180 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, gaming) dataset of 9,794 users and 28,073 reply edges from 69,478 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 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 Voat (Reddit alternative, 2013–2020) dataset of 4,499 submissions, 13,290 comments, 3,047 users, 5,232 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/GamerGate, covering its full lifetime on the platform (2013–2020). Includes all 4,499 submissions and 13,290 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Voat (Reddit alternative, 2013–2020) dataset of 4,716 submissions, 7,058 comments, 1,450 users, 1,535 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/gamingfringe, covering its full lifetime on the platform (2013–2020). Includes all 4,716 submissions and 7,058 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Amazon dataset of 13,307 QA pairs in Video Games, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Video Games. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
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.
A Chess game records (professional matches) dataset of 7,301 nodes and 60,046 edges, collected by KONECT via chess game database. Each record contains directed: True, weighted: True, signed: True. Directed network of chess game outcomes: edges go from winner to loser, with timestamps. Draws encoded as 0 weight.. Suitable for competition network analysis, ranking algorithms, temporal network analysis.
A Wikispeedia (Wikipedia-based online navigation game) dataset of 4,586 Wikipedia article nodes, 119,767 hyperlinks, and 76,193 human navigation paths, collected by West & Leskovec via the Wikispeedia online game (2008–2012). Each record contains article hyperlink graph (source → target), navigation path sequences, path duration in seconds, path length in clicks, back-click count, and optional difficulty rating (1=easy to 5=brutal). Unique dataset combining a Wikipedia hyperlink graph with 76,193 human navigation paths from an online game where players navigate from a random start article to a target article using only hyperlinks — 67.4% of paths were successfully completed.. Suitable for semantic distance estimation, human wayfinding behavior, hyperlink graph analysis, information foraging, Wikipedia structure research.
A Twitch dataset of 1,000 top streamers with viewership and engagement metrics, collected by Aayush Mishra via Twitch API (2020). Each record contains channel name, watch time, streaming time, max/average viewers, followers, followers gained, views gained, partnership status, age-restriction status, and language. A comprehensive snapshot of the top 1,000 Twitch streamers, capturing key engagement and growth metrics for the platform's most influential content creators. Suitable for influencer analysis, engagement prediction, platform dynamics, streamer growth modeling, gaming community studies.