A Parler (alternative social network) dataset of ~183,000,000 posts from Parler's full history before deplatforming, collected by Aliapoulios et al. via Parler API (2021). Each record contains post body text, username, timestamp, hashtags, upvotes, reposts, impressions, comment count, sensitive flag, media attachments, reply depth, parent post ID. Complete Parler post archive from before the platform's deplatforming — includes Jan 6 Capitol riot content, far-right discourse, and cross-posts from Twitter. Suitable for deplatforming research, far-right discourse analysis, January 6th research, hate speech detection, alternative platform behavior, content moderation effects.
A 4chan /pol/ (Politically Incorrect board) dataset of 134,529,233 posts across 3,397,911 threads (4,894,179 with 7-score Perspective API annotations), collected by Papasavva et al. via 4chan API + Perspective API (2020). Each record contains post text (com), thread ID, post number, country, timestamp, image metadata, 7 Perspective API scores (TOXICITY, SEVERE_TOXICITY, INFLAMMATORY, PROFANITY, INSULT, OBSCENE, SPAM), named entities. 134,529,233 4chan /pol/ posts with per-post Perspective API toxicity scores across 7 dimensions — one of the most comprehensively annotated fringe platform datasets covering 3.5 years of /pol/ discourse. Suitable for toxicity measurement, hate speech analysis, fringe platform research, political discourse on imageboards, cross-platform toxicity comparison, longitudinal hate speech trends.
A Telegram (German-language conspiracy channels) dataset of 63,908,365 messages from 4,404 unique channels, collected by Hagen, Wiencierz, and Freudenthaler via Telegram API. Each record contains message UUID, channel name, author, reply structure, conspiracy label, language, media type (photo/video/voice), audio/video duration, forwarding metadata, duplicate flag. Schwurbelarchiv is a large-scale German Telegram corpus with 3.1% of messages labeled as conspiracy content, 23.8% reply edges enabling thread analysis, and rich media metadata across 4,404 channels. Suitable for conspiracy theory detection, German NLP, social network analysis, Telegram platform research, misinformation propagation, reply network analysis, media sharing patterns.
A MADOC (Reddit, funny) dataset of 3,851,024 users and 21,255,711 reply edges from 61,859,095 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). FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Suitable for social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
A MADOC (Reddit, pics) dataset of 3,453,264 users and 15,863,415 reply edges from 51,914,975 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). FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Suitable for social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.
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, videos) dataset of 1,854,456 users and 8,653,524 reply edges from 36,775,460 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 Gab (alt-right social network) dataset of 22,112,812 Gab posts from January 2018 (13,871,421 original posts, 8,241,391 reposts), collected by Zannettou et al. via Gab API (2018). Each record contains post body text, username, verified flag, published_at, post type (post/repost), topic category, language, likes/reposts/replies counts, sentiment score, isPopular. 22,112,812 Gab posts from January 2018 — one of the earliest large-scale Gab datasets, capturing the platform during its growth phase as an alt-right Twitter alternative. Suitable for alt-right discourse analysis, fringe platform research, meme propagation, hate speech detection, cross-platform information flow, deplatforming research.
A MADOC (Reddit, gifs) dataset of 1,894,135 users and 6,785,726 reply edges from 21,090,022 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.
Posts from 329 thematically distinct 'general' thread collections on 4chan's /pol/ board, November 2013 to May 2019, released by Emilija Jokubauskaitė and Stijn Peeters (Zenodo 3603292). 13,756,579 posts in 58,687 threads, one CSV per general plus an index file. Each row holds the thread ID, post ID, timestamp, body text, subject, poster name, image file name and MD5, and the poster's country code and name. Suitable for studying recurring political discussion threads, propaganda, hate speech and online subcultures.
A Parler (alternative social network) dataset of 13,254,060 Parler user profiles with bios and activity metrics, collected by Aliapoulios et al. via Parler API (2021). Each record contains user ID, username, bio text, follower/following counts, post/comment/like/media counts, join date, verified/banned/human flags. 13,254,060 Parler user profiles from the platform's peak period before its deplatforming — 605 verified accounts, 287,391 banned users. Suitable for deplatforming research, far-right social network analysis, user behavior on alternative platforms, bot detection, political communication research.
A MADOC (Reddit, technology) dataset of 611,131 users and 2,052,369 reply edges from 11,766,082 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 Reddit dataset of 8,035,392 comments across 6 financial subreddits, 2008–2020, collected by Zenodo contributor via Pushshift Reddit API. Each record contains body text, subreddit, author, created_date, year, readability metrics (Fog index, avg words/sentence, avg syllables/word). 8M+ Reddit comments from r/personalfinance, r/Frugal, r/Economics, r/business, r/investing, and r/financialindependence spanning 2008–2020, pre-annotated with Gunning Fog readability scores.. Suitable for Financial discourse analysis, readability research, community language evolution, NLP on financial social media..
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 MADOC (Reddit, CringeAnarchy) dataset of 202,705 users and 1,864,741 reply edges from 6,445,396 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 Reddit dataset of 6,252,711 posts and comments, 6,279 AITA submissions, 6,239,711 nodes, 6,133,386 reply edges, collected by Zenodo contributor via Reddit API, September–October 2023. Each record contains post/comment id, reply graph (parent_id), title, VADER sentiment, readability (Fog + FK-GL), 10 emotion lexicon scores (anticipation, disgust, fear, joy, sadness, surprise, trust, anger, positive, negative), valence/arousal/dominance. 2M+ r/AmITheAsshole posts and comments with pre-computed emotion lexicon scores, readability metrics, and VADER sentiment across multiple time windows (all-time, monthly, weekly, yearly); includes full reply graph structure.. Suitable for Emotion dynamics in online moral judgment, reply network analysis, readability and engagement research, temporal thread growth modeling..
A MADOC (Koo, koo) dataset of 124,477 users and 1,121,958 reply edges from 4,263,640 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.
Moltbook, a social network whose members are autonomous AI agents (Hugging Face jscmp4/Moltbook, 2025): 100,590 agent profiles, 3,352,520 posts and 16,663,266 comments. The graph links agents to the posts and comments they wrote and comments to their posts (20,199,253 nodes, 36,678,988 edges). Suitable for research on AI agent behaviour and social dynamics.
A MADOC (Reddit, MensRights) dataset of 113,904 users and 822,329 reply edges from 3,110,425 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 552,155 submissions, 2,506,862 comments, 57,280 users, 934,284 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. Thematic cluster of 75 Voat subverses covering voat far-right politics communities, combining 552,155 submissions and 2,506,862 comments into a single user collaboration network for cross-community analysis.. Suitable for cross-community analysis, topic modeling, platform dynamics, social network analysis, content moderation research.
A Voat (Reddit alternative, 2013–2020) dataset of 476,656 submissions, 2,465,643 comments, 74,909 users, 1,095,198 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. Thematic cluster of 75 Voat subverses covering voat general discussion communities, combining 476,656 submissions and 2,465,643 comments into a single user collaboration network for cross-community analysis.. Suitable for cross-community analysis, topic modeling, platform dynamics, social network analysis, content moderation research.
A MADOC (Bluesky, bluesky) dataset of 164,265 users and 894,917 reply edges from 2,814,352 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 Incels.co (manosphere forum) dataset of 2,436,297 posts from 5,933 unique authors across 117,592 threads, collected by Farrell et al. via web crawl (2019-2020). Each record contains post text, author username, author title/flair, join date, post count, post timestamp, thread URL, reply interactions, embedded links. Incels.co dataset contains 2,436,297 forum posts from 2017-11 to 2019-06, part of the iDRAMA manosphere collection covering incel and anti-feminist communities. Suitable for misogyny detection, hate speech research, radicalization analysis, manosphere community studies, extremist forum analysis, NLP classification, social network analysis.
Posts from v/QRV, the QAnon research subverse on Voat, 2018-2020, from the Voat archive of Mekacher & Papasavva (ICWSM 2022): 187,158 submissions and 2,229,684 comments with their text, votes and dates. The archive did not recover the author of almost any v/QRV post (it writes a placeholder instead), so this entry has no user or reply graph. Suitable for QAnon and conspiracy discourse, topic modelling and moderation research.
A Slashdot dataset of 10,019 discussion threads, August 2005 to August 2006, from the Online Conversation Threads repository of Aragón et al. (ICWSM 2017): 2,084,864 nodes (articles and comments) and 2,075,611 comment-to-parent reply edges, with comment text, moderation scores, timestamps and thread depth. Suitable for online discourse analysis, conversation dynamics and hierarchical reply-tree structure.
A Voat (Reddit alternative, 2013–2020) dataset of 193,600 submissions, 1,478,207 comments, 32,586 users, 674,908 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. Aggregate of Voat communities containing explicit hate speech targeting racial, religious, and other minority groups. Included for research transparency — enables hate speech detection, toxicity modeling, and online radicalization studies using real platform data.. Suitable for hate speech detection, toxicity modeling, online radicalization, content moderation research, platform dynamics.
A Manosphere forum (Roosh V Forum) dataset of 1,492,561 posts from 13,599 unique authors on Roosh V Forum, collected by Ribeiro et al. via web crawl (2021). Each record contains post text (text_post), author (author), timestamp, post metadata. 1,492,561 posts from Roosh V Forum — part of the Evolution of the Manosphere dataset covering incel, MGTOW, PUA, and related anti-feminist communities across 9 forums. Suitable for manosphere discourse analysis, incel radicalization research, hate speech detection, community evolution, misogynistic content analysis, toxicity measurement.
A MADOC (Reddit, fatpeoplehate) dataset of 1,409,008 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 twitter dataset of 1,352,000 Spanish tweet IDs from Pride Day (June 28) across 11 years, collected by Ramiro Ortega and Hassan (2025). Each record contains tweet IDs, LGBTIQ+ vs random label — full content requires hydration. 10-year longitudinal Spanish-language Pride Day dataset enabling temporal hate speech trend analysis. Suitable for hate speech detection, temporal discourse analysis, LGBTIQ+ online safety, Spanish NLP.
A Reddit (r/teaching community) dataset of 1,304,575 comments from r/teaching with 5-class sentiment scores, pre/post COVID labels (438,027 pre, 866,548 post), and relational language detection, collected by Cai et al. via Reddit API (2024). Each record contains comment text, post title, post selftext, created_utc, score, reply_count, pandemic_period (0=pre/1=post COVID), predicted_rating (1-5), normalized_sentiment (-1 to +1), contains_relational_word, sentiment_probabilities. 1,304,575 r/teaching comments with fine-grained 5-class sentiment analysis spanning pre/post COVID — enabling longitudinal study of how teaching community discourse and emotional tone shifted during the pandemic. Suitable for community sentiment analysis, COVID-19 discourse shifts, longitudinal NLP, education community research, relational language detection, sentiment classification.
A snapshot of Truth Social from February to September 2022, released by Patrick Gerard, Nicholas Botzer and Tim Weninger (University of Notre Dame) on Zenodo (7522646). 454,458 users and 845,060 posts ('truths'), with 4,002,115 follow edges, 506,276 replies and 10,508 quotes, plus hashtags, media and external URLs, as 13 tab-separated tables. Suitable for social network analysis, political communication and misinformation research on an alternative platform.
A MADOC (Reddit, milliondollarextreme) dataset of 19,187 users and 422,964 reply edges from 1,286,148 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 176,948 submissions, 1,081,119 comments, 36,459 users, 469,843 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/news, covering its full lifetime on the platform (2013–2020). Includes all 176,948 submissions and 1,081,119 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 182,954 submissions, 978,568 comments, 30,024 users, 478,797 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/whatever, covering its full lifetime on the platform (2013–2020). Includes all 182,954 submissions and 978,568 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Twitter (#NoMore hashtag campaign) dataset of 1,048,574 tweets from the Ethiopian #NoMore movement (2021-11 to 2022-08), collected by Zenodo contributors via Twitter API. Each record contains tweet text, language, timestamp; Amharic+English bilingual subset also available. 1,048,574 tweets covering the #NoMore solidarity movement in Ethiopia and Eritrea — one of few African social movement datasets with Amharic content, spanning 2021-11 to 2022-08. Suitable for African social movement analysis, multilingual NLP, Amharic text processing, political communication research, hashtag activism, Global South social media studies.
A Last.fm dataset of 976741 users, 3151283 friendships, 10.9M annotations, collected by Kompan and Bielikova, first half of 2009. Each record contains user friendship graph, user-item-tag annotations, group membership, neighbourhood scores. Last.fm social network with 99k users, 10.9M music annotations, 281k tags, and 66k groups from H1 2009.. Suitable for Social influence analysis, music recommendation, tag-based community detection..
A Voat (Reddit alternative, 2013–2020) dataset of 148,629 submissions, 844,982 comments, 30,049 users, 341,970 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/politics, covering its full lifetime on the platform (2013–2020). Includes all 148,629 submissions and 844,982 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
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.
A Voat (Reddit alternative, 2013–2020) dataset of 76,234 submissions, 884,260 comments, 22,900 users, 484,401 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/fatpeoplehate, covering its full lifetime on the platform (2013–2020). Includes all 76,234 submissions and 884,260 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 103,156 submissions, 844,868 comments, 15,037 users, 280,241 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/GreatAwakening, covering its full lifetime on the platform (2013–2020). Includes all 103,156 submissions and 844,868 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Manosphere forum (Red Pill Talk) dataset of 884,001 posts from 7,900 unique authors on Red Pill Talk, collected by Ribeiro et al. via web crawl (2021). Each record contains post text (text_post), author (author), timestamp, post metadata. 884,001 posts from Red Pill Talk — part of the Evolution of the Manosphere dataset covering incel, MGTOW, PUA, and related anti-feminist communities across 9 forums. Suitable for manosphere discourse analysis, incel radicalization research, hate speech detection, community evolution, misogynistic content analysis, toxicity measurement.
A Voat (Reddit alternative, 2013–2020) dataset of 159,697 submissions, 524,549 comments, 39,227 users, 238,664 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. Thematic cluster of 70 Voat subverses covering voat media & entertainment communities, combining 159,697 submissions and 524,549 comments into a single user collaboration network for cross-community analysis.. Suitable for cross-community analysis, topic modeling, platform dynamics, social network analysis, content moderation research.
Posts from v/8chan on Voat, from the Voat archive of Mekacher & Papasavva (ICWSM 2022): 5,804 submissions and 630,059 comments with their text, votes and dates. The archive did not recover the author of almost any post in this subverse, so the entry has no user or reply graph. Suitable for studying anonymous posting, topic modelling and moderation.
A Voat (Reddit alternative, 2013–2020) dataset of 51,082 submissions, 431,297 comments, 34,340 users, 252,920 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/AskVoat, covering its full lifetime on the platform (2013–2020). Includes all 51,082 submissions and 431,297 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 54,170 submissions, 382,422 comments, 11,439 users, 130,857 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/theawakening, covering its full lifetime on the platform (2013–2020). Includes all 54,170 submissions and 382,422 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Twitter dataset of 404,615 nodes, 434,963 edges, collected by Pierri et al. (OSoMe/Indiana University + Politecnico di Milano), 2020. Each record contains retweet network (uid1, uid2), user-domain bipartite network, user co-sharing network. Twitter news-sharing network revealing information polluters through retweet and co-sharing patterns.. Suitable for Information polluter identification, news sharing network analysis, source credibility..
A Voat (Reddit alternative, 2013–2020) dataset of 36,749 submissions, 341,207 comments, 16,507 users, 152,119 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/pizzagate, covering its full lifetime on the platform (2013–2020). Includes all 36,749 submissions and 341,207 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
A Twitter dataset of 2,280 user accounts, 368,028 tweets, collected by Yang and Menczer (OSoMe/Indiana University), 2023. Each record contains user_id, label (bot/human), dataset source, full tweet objects with text and metadata. First large-scale dataset of AI-powered social bots (Fox8 botnet) with GPT-generated tweet content; includes human baseline accounts for comparison.. Suitable for AI bot detection, LLM-generated content identification, social botnet analysis..
A Voat (Reddit alternative, 2013–2020) dataset of 46,877 submissions, 365,857 comments, 26,883 users, 193,345 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/funny, covering its full lifetime on the platform (2013–2020). Includes all 46,877 submissions and 365,857 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.
Parler
4chan
Telegram
Reddit
YouTube
Gab
Koo
Moltbook
Voat
Bluesky
Incels.co
Slashdot
Twitter (X)
Truth Social
Last.fm