CC BY 4.0

196 datasets tagged as the license “CC BY 4.0”.

196 datasets — page 2 of 4.

MADOC: Voat / fatpeoplehate Analyzed

A MADOC (Voat, fatpeoplehate) dataset of 20,942 users and 226,749 reply edges from 352,003 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.

351.9K records20.9K nodes226.7K edges2025

MADOC: Voat / greatawakening Analyzed

A MADOC (Voat, greatawakening) dataset of 11,863 users and 155,890 reply edges from 324,835 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.

324.8K records11.9K nodes155.9K edges2025

Voat Long-Tail Communities (>100KB subverses) Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 127,238 submissions, 196,710 comments, 19,786 users, 80,559 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 190 smaller Voat subverses (>100KB each) not covered by individual or thematic cluster entries. Represents the breadth of the platform beyond its headline communities, combining 127,238 submissions and 196,710 comments.. Suitable for platform breadth analysis, long-tail community dynamics, niche community research, social network analysis.

310.2K records19.8K nodes80.6K edges2022

Reddit Corpus (Small) — 100 Active Subreddits Analyzed

A Reddit dataset of 297,132 utterances from 119,889 speakers across 100 subreddits, collected by Cornell University via ConvoKit. Each record contains utterance text, speaker, conversation thread, subreddit. Conversation corpus from 100 active subreddits with thread structure. Suitable for conversation analysis, community dynamics, discourse analysis.

297.1K records2020

Voat — v/Niggers Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 41,816 submissions, 271,441 comments, 9,111 users, 112,835 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/Niggers, covering its full lifetime on the platform (2013–2020). Includes all 41,816 submissions and 271,441 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

294.7K records9.1K nodes112.8K edges2022

SMIDGE Telegram Disinformation Dataset Analyzed

A Telegram (86 disinformation/conspiracy channels) dataset of 279,682 cleaned messages across 83 channels, collected by Federation of American Scientists via Telegram API. Each record contains message text (cleaned), channel name, timestamp, extracted URL, domain, and detected language per message. SMIDGE is a curated Telegram corpus spanning 2023-09-25 to 2024-09-24, focused on 83 channels selected for disinformation and conspiracy content, with 5,334 unique domains linked. Suitable for disinformation detection, conspiracy theory analysis, NLP text classification, content moderation, cross-platform information spread research.

279.7K records2026

MonkeyPox2022Tweets Limited

A twitter dataset of 255,363 tweet IDs about the 2022 monkeypox outbreak, collected by Thakur (University of Cincinnati, 2022). Each record contains tweet IDs only — full content requires hydration. First public Twitter dataset on the 2022 monkeypox outbreak, enabling early-stage disease discourse analysis. Suitable for disease surveillance, public health communication, health misinformation.

255.4K records2022

Manosphere Dataset — A Voice For Men Analyzed

A Manosphere forum (A Voice For Men) dataset of 211,070 posts from 1,802 unique authors on A Voice For Men, collected by Ribeiro et al. via web crawl (2021). Each record contains post text (text_post), author (author), timestamp, post metadata. 211,070 posts from A Voice For Men — 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.

211.1K records1.8K nodes1.8K edges2021

Voat — v/videos Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 44,923 submissions, 153,181 comments, 18,935 users, 89,631 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/videos, covering its full lifetime on the platform (2013–2020). Includes all 44,923 submissions and 153,181 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

183K records18.9K nodes89.6K edges2022

Voat — v/technology Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 34,801 submissions, 152,719 comments, 18,114 users, 77,540 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/technology, covering its full lifetime on the platform (2013–2020). Includes all 34,801 submissions and 152,719 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

178.1K records18.1K nodes77.5K edges2022

Barrapunto Online Conversation Threads (Jan 2005–Dec 2007) Analyzed

A Barrapunto (the Spanish Slashdot) dataset of 7,724 discussion threads, 2005-2007, from the Online Conversation Threads repository of Aragón et al. (ICWSM 2017): 172,132 nodes (articles and comments) and 169,825 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.

172.1K records172.1K nodes169.8K edges2008

Voat — v/NeoFAG Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 23,694 submissions, 151,624 comments, 3,486 users, 34,151 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/NeoFAG, covering its full lifetime on the platform (2013–2020). Includes all 23,694 submissions and 151,624 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

171.2K records3.5K nodes34.2K edges2022

Voat — v/gaming Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 28,755 submissions, 139,916 comments, 17,940 users, 75,975 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 28,755 submissions and 139,916 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

162K records17.9K nodes76K edges2022

MADOC: Voat / funny Analyzed

A MADOC (Voat, funny) dataset of 17,128 users and 82,319 reply edges from 143,945 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.

143.9K records17.1K nodes82.3K edges2025

What Makes Programmers Laugh? r/ProgrammerHumor Dataset (ESEM 2024) Analyzed

A Reddit dataset of 139,718 posts from r/ProgrammerHumor, 2014–2022, collected by Noei, Gauthier-Ouellet, Adams (Queen's University) via Reddit API. Each record contains post text (OCR for images), title, score, scoreratio, ncomments, post type (image/text/link), timestamp, LDA topic ID, virality label. 139k r/ProgrammerHumor submissions (2014–2022) with LDA topic labels, engagement metrics, and binary virality labels; replication package for ESEM 2024 paper on humor in software communities.. Suitable for Humor detection, community engagement analysis, software discourse, LDA topic modeling validation..

139.7K records2024

Voat — v/Conspiracy Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 25,989 submissions, 94,638 comments, 10,272 users, 46,388 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/Conspiracy, covering its full lifetime on the platform (2013–2020). Includes all 25,989 submissions and 94,638 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

117.1K records10.3K nodes46.4K edges2022

Voat — v/SoapboxBanhammer Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 33,774 submissions, 87,664 comments, 3,508 users, 15,643 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/SoapboxBanhammer, covering its full lifetime on the platform (2013–2020). Includes all 33,774 submissions and 87,664 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

110.7K records3.5K nodes15.6K edges2022

Voat Lifestyle & Hobbies Communities Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 36,079 submissions, 78,000 comments, 14,765 users, 44,437 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 49 Voat subverses covering voat lifestyle & hobbies communities, combining 36,079 submissions and 78,000 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.

109.6K records14.8K nodes44.4K edges2022

Voat Religion & Philosophy Communities Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 31,879 submissions, 69,349 comments, 8,662 users, 24,461 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 28 Voat subverses covering voat religion & philosophy communities, combining 31,879 submissions and 69,349 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.

100.5K records8.7K nodes24.5K edges2022

Voat — v/OccidentalEnclave Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 30,530 submissions, 68,820 comments, 4,178 users, 13,926 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/OccidentalEnclave, covering its full lifetime on the platform (2013–2020). Includes all 30,530 submissions and 68,820 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

96.6K records4.2K nodes13.9K edges2022

Voat — v/AnonAll Analyzed

Posts from v/AnonAll on Voat, from the Voat archive of Mekacher & Papasavva (ICWSM 2022): 34,658 submissions and 65,541 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.

95.1K records2022

TruthStance: Truth Social User Dataset Analyzed

A Truth Social (user account corpus) dataset of 90,683 user accounts with 1,611 verified and 0 bot-labeled, collected by TruthStance project team via Truth Social API. Each record contains username, follower/following counts, account creation date, profile bio text, bot label, verified status. TruthStance covers 90,683 Truth Social accounts spanning 2022-02 to 2025-12, with 1,611 verified accounts and 61,226 users with bio text — one of few datasets focused on Truth Social platform users. Suitable for Truth Social platform analysis, bot detection, political social media research, user behavior modeling, alternative platform studies.

90.7K records2026

Voat — v/pics Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 14,882 submissions, 87,143 comments, 14,833 users, 52,174 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/pics, covering its full lifetime on the platform (2013–2020). Includes all 14,882 submissions and 87,143 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

89.7K records14.8K nodes52.2K edges2022

Voat — v/Science Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 13,518 submissions, 79,352 comments, 11,533 users, 41,095 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/Science, covering its full lifetime on the platform (2013–2020). Includes all 13,518 submissions and 79,352 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

86.2K records11.5K nodes41.1K edges2022

MADOC: Voat / videos Analyzed

A MADOC (Voat, videos) dataset of 10,756 users and 31,132 reply edges from 85,197 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.

85.2K records10.8K nodes31.1K edges2025

MADOC: Voat / technology Analyzed

A MADOC (Voat, technology) dataset of 14,397 users and 41,519 reply edges from 83,185 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.

83.2K records14.4K nodes41.5K edges2025

Voat — v/Worldnews Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 20,237 submissions, 63,811 comments, 7,956 users, 33,170 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/Worldnews, covering its full lifetime on the platform (2013–2020). Includes all 20,237 submissions and 63,811 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

78.8K records8K nodes33.2K edges2022

Voat — v/MeanwhileOnReddit Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,241 submissions, 72,721 comments, 11,778 users, 43,492 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/MeanwhileOnReddit, covering its full lifetime on the platform (2013–2020). Includes all 8,241 submissions and 72,721 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

75.3K records11.8K nodes43.5K edges2022

Synthetic Cyberbullying and Toxic Span Dataset Analyzed

Synthetic, templated data: 75,000 short texts labelled with one of 6 harassment categories or non-toxic (10,714 or 10,715 each), with a 'platform' value (Facebook, Instagram, Reddit, news portal) and character offsets of the toxic span. The texts are generated from a small set of templates: the toxic rows use only 30 distinct toxic phrases, and every row ends in a '(Ref Node: #NNNNNN)' token. The platform values are assigned, not observed. Published on Mendeley Data. Suitable for testing span-tagging code, not for measuring real cyberbullying.

75K records2026

MADOC: Voat / gaming Analyzed

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.

69.5K records9.8K nodes28.1K edges2025

Voat — v/TheDonald Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 14,203 submissions, 58,896 comments, 7,657 users, 32,084 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/TheDonald, covering its full lifetime on the platform (2013–2020). Includes all 14,203 submissions and 58,896 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

68.3K records7.7K nodes32.1K edges2022

Voat — v/HDLunited Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 5,413 submissions, 69,248 comments, 4,003 users, 20,403 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/HDLunited, covering its full lifetime on the platform (2013–2020). Includes all 5,413 submissions and 69,248 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

66.6K records4K nodes20.4K edges2022

Voat — v/introductions Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 12,382 submissions, 47,518 comments, 17,222 users, 37,102 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/introductions, covering its full lifetime on the platform (2013–2020). Includes all 12,382 submissions and 47,518 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

62.4K records17.2K nodes37.1K edges2022

OffensEval 2020 — All Languages Combined Analyzed

A Twitter (OffensEval 2020 — 5 languages) dataset of 61,922 tweets across 5 languages with offensive/non-offensive labels, collected by Zampieri et al. for SemEval-2020 Task 12. Each record contains tweet text, binary offensive label (OFF/NOT), language, split. Combined OffensEval 2020 benchmark across Arabic, Danish, English, Greek, and Turkish — 61,922 tweets from the most-participated SemEval task ever (528 teams). Suitable for multilingual offensive language detection, cross-lingual transfer, content moderation, NLP benchmarking.

61.9K records2020

Social Bookmarking Dataset — GiveALink November 2009 Analyzed

A Delicious dataset of 61,665 bookmarks, collected by OSoMe / GiveALink project, November 2009. Each record contains bookmark URL, timestamp, user tags. Daily Delicious social bookmarking snapshots from November 2009; each bookmark includes URL, Unix timestamp, and free-form user tags.. Suitable for Social bookmarking analysis, tag-based topic modeling, information diffusion, temporal content analysis..

61.7K records2006

NaijaSenti: Nigerian Twitter Sentiment Corpus Limited

A Twitter (Nigerian language communities) dataset of 60,823 tweet IDs across 4 Nigerian languages with sentiment labels, collected by Muhammad et al. via Twitter API (2022). Each record contains tweet ID, sentiment label (positive/negative/neutral), language, split (train/dev/test). First large-scale sentiment corpus for Nigerian languages — 60,823 annotated tweet IDs across Hausa, Igbo, Yoruba, and Nigerian Pidgin, enabling low-resource African NLP research.. Suitable for low-resource NLP, African language sentiment analysis, multilingual classification, cross-lingual transfer..

60.8K records2022

Voat — v/European Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 13,895 submissions, 49,271 comments, 4,486 users, 22,205 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/European, covering its full lifetime on the platform (2013–2020). Includes all 13,895 submissions and 49,271 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

60.5K records4.5K nodes22.2K edges2022

Voat — v/soapdoxbanhammer Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 17,368 submissions, 47,467 comments, 1,963 users, 7,593 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/soapdoxbanhammer, covering its full lifetime on the platform (2013–2020). Includes all 17,368 submissions and 47,467 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

58.5K records2K nodes7.6K edges2022

Voat — v/music Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 25,680 submissions, 33,410 comments, 7,717 users, 17,094 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/music, covering its full lifetime on the platform (2013–2020). Includes all 25,680 submissions and 33,410 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

56.1K records7.7K nodes17.1K edges2022

Voat — v/gifs Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,024 submissions, 56,794 comments, 11,268 users, 32,641 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/gifs, covering its full lifetime on the platform (2013–2020). Includes all 8,024 submissions and 56,794 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

55.4K records11.3K nodes32.6K edges2022

Voat — v/AnonTalk Analyzed

Posts from v/AnonTalk on Voat, from the Voat archive of Mekacher & Papasavva (ICWSM 2022): 10,459 submissions and 47,670 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.

53.9K records2022

Voat — v/Showerthoughts Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,902 submissions, 45,273 comments, 6,641 users, 27,324 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/Showerthoughts, covering its full lifetime on the platform (2013–2020). Includes all 8,902 submissions and 45,273 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

53K records6.6K nodes27.3K edges2022

Voat — v/WTF Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,037 submissions, 48,414 comments, 7,630 users, 27,404 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/WTF, covering its full lifetime on the platform (2013–2020). Includes all 8,037 submissions and 48,414 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

50K records7.6K nodes27.4K edges2022

Voat — v/Identitarian Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 9,712 submissions, 41,626 comments, 3,345 users, 20,765 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/Identitarian, covering its full lifetime on the platform (2013–2020). Includes all 9,712 submissions and 41,626 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

49.1K records3.3K nodes20.8K edges2022

Voat — v/movies Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 8,458 submissions, 41,142 comments, 8,403 users, 24,105 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/movies, covering its full lifetime on the platform (2013–2020). Includes all 8,458 submissions and 41,142 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

47.3K records8.4K nodes24.1K edges2022

Voat — v/milliondollarextreme Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 7,351 submissions, 43,236 comments, 3,637 users, 23,227 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/milliondollarextreme, covering its full lifetime on the platform (2013–2020). Includes all 7,351 submissions and 43,236 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

45.3K records3.6K nodes23.2K edges2022

Voat — v/4chan Analyzed

A Voat (Reddit alternative, 2013–2020) dataset of 3,617 submissions, 44,794 comments, 5,726 users, 18,506 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/4chan, covering its full lifetime on the platform (2013–2020). Includes all 3,617 submissions and 44,794 comments with full text and engagement metadata.. Suitable for social network analysis, community dynamics, content moderation, platform migration studies, online community research.

42.5K records5.7K nodes18.5K edges2022

Slack Software Conversations (MSR 2020) Analyzed

A Slack (software development communities) dataset of 40,010 messages across 5 programming language communities, collected by Chattopadhyay et al. for MSR 2020. Each record contains Slack message text, timestamp, speaker (anonymized), thread, community. Multi-community Slack dataset from software development channels, including Elmlang, Clojurians, Python, and Racket communities.. Suitable for conversation analysis, community dynamics, technical communication, linguistic analysis of developer chat.

40K records2020

MADOC: Voat / pics Analyzed

A MADOC (Voat, pics) dataset of 7,712 users and 18,229 reply edges from 38,555 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.

38.6K records7.7K nodes18.2K edges2025

PHEME Rumour Dataset — charliehebdo Analyzed

Twitter conversations around the Charlie Hebdo shooting in Paris (January 2015), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 2,079 threads, each a source tweet and its replies, of which 458 were judged rumours by journalists and 1,621 not. Every rumour also carries its veracity as later established: 193 true, 116 false and 149 unverified. 38,268 tweets in all, with full tweet JSON. ECHO builds the reply network (36,189 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.

38.3K records38.7K nodes36.2K edges2018