Text

798 datasets tagged as the data type “Text”.

798 datasets — page 6 of 16.

YouTube Snapshot 080725 Analyzed

A YouTube dataset of 78,441 videos, 990,681 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080725 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

517.3K records517.3K nodes990.7K edges2008

YouTube Snapshot 080609 Analyzed

A YouTube dataset of 77,528 videos, 950,829 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080609 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

512.7K records512.7K nodes950.8K edges2008

YouTube Snapshot 080526 Analyzed

A YouTube dataset of 72,944 videos, 937,523 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080526 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

511K records511K nodes937.5K edges2008

YouTube Snapshot 080617 Analyzed

A YouTube dataset of 74,490 videos, 904,570 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080617 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

506.8K records506.8K nodes904.6K edges2008

YouTube Snapshot 080613 Analyzed

A YouTube dataset of 71,912 videos, 931,141 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080613 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

504.9K records504.9K nodes931.1K edges2008

YouTube Snapshot 080719 Analyzed

A YouTube dataset of 72,702 videos, 867,579 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080719 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

502.8K records502.8K nodes867.6K edges2008

Stack Exchange — rpg.stackexchange.com Analyzed

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..

500.3K records20.1K nodes84.7K edges2025

Sentiment140 Tweet Sentiment Dataset Analyzed

A Twitter dataset of 1,600,000 tweets with binary sentiment labels (positive/negative) assigned via emoticon distant supervision, collected by Go, Bhayani and Huang at Stanford University via Twitter streaming API in 2009. Each record contains tweet text with polarity label (0=negative, 4=positive), tweet ID, timestamp, search query used for collection, and username. The dataset is notable for its one of the largest and most widely used Twitter sentiment benchmarks, notable for using emoticons as a noisy but scalable distant supervision signal rather than manual annotation, enabling 1.6M labeled examples. Intended for research into sentiment analysis, opinion mining, distant supervision research, text classification benchmarking, and social media language modeling.

500K records2009

4chanpol OpenAIMod Dataset (500k posts) Analyzed

A 4chan (/pol/) dataset of 499,723 posts with moderation scores, collected by kjj0 via 4chan API and OpenAI moderation model. Each record contains post text, sexual score, hate score, violence score, self-harm score, sexual/minors score, hate/threatening score, violence/graphic score. A dataset of 500,000 /pol/ posts with OpenAI moderation scores, enabling research on content moderation, hate speech detection, and harmful content analysis. Suitable for content moderation, hate speech detection, toxicity analysis, misinformation, political communication.

499.7K records2020

YouTube Snapshot 080611 Analyzed

A YouTube dataset of 70,150 videos, 865,359 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080611 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

492.4K records492.4K nodes865.3K edges2008

YouTube Snapshot 080530 Analyzed

A YouTube dataset of 71,619 videos, 878,376 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080530 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

491.5K records491.5K nodes878.4K edges2008

YouTube Snapshot 080504 Analyzed

A YouTube dataset of 69,101 videos, 901,845 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080504 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

491.4K records491.4K nodes901.8K edges2008

YouTube Snapshot 080426 Analyzed

A YouTube dataset of 68,060 videos, 922,486 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080426 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

489.8K records489.8K nodes922.5K edges2008

YouTube Snapshot 080619 Analyzed

A YouTube dataset of 72,362 videos, 865,092 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080619 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

489.2K records489.2K nodes865K edges2008

YouTube Snapshot 0515 Analyzed

A YouTube dataset of 45,004 videos, 879,478 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0515 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

488.7K records488.7K nodes879.5K edges2008

Stack Exchange — travel.stackexchange.com Analyzed

A Stack Exchange (travel.stackexchange.com) dataset of 31,218 users, 61,029 answer-collaboration edges, 48,768 questions, 76,736 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 travel.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..

484.4K records31.2K nodes61K edges2025

Voat — v/AskVoat Analyzed

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.

464.8K records34.3K nodes252.9K edges2022

YouTube Snapshot 080711 Analyzed

A YouTube dataset of 65,221 videos, 839,055 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080711 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

464.5K records464.5K nodes839.1K edges2008

YouTube Snapshot 080601 Analyzed

A YouTube dataset of 69,833 videos, 843,828 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080601 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

462.8K records462.8K nodes843.8K edges2008

YouTube Snapshot 0322 Analyzed

A YouTube dataset of 52,998 videos, 974,357 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0322 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

461.7K records461.7K nodes974.4K edges2008

YouTube Snapshot 080615 Analyzed

A YouTube dataset of 68,662 videos, 839,427 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080615 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

461.7K records461.7K nodes839.4K edges2008

Pushshift Reddit — 2008-09 Analyzed

A Reddit (Pushshift archive, 2008-09) dataset of 261,881 comments and 199,295 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 665 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-09 — full comment text, reply graph, and engagement metrics across 665 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.

459.4K records261.9K nodes199.3K edges2020

YouTube Snapshot 0327 Analyzed

A YouTube dataset of 50,861 videos, 949,407 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0327 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

449.8K records449.8K nodes949.4K edges2008

YouTube Snapshot 080627 Analyzed

A YouTube dataset of 65,799 videos, 824,507 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080627 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

444.3K records444.3K nodes824.5K edges2008

Instagram Influencer Dataset — Beauty Analyzed

A Instagram (beauty influencers) dataset of 436,843 posts from beauty influencers, collected by Seungbae Kim and Jinyoung Han (2020). Each record contains post caption text, like count, comment count, video/ad flags, tagged user count, location presence, image dimensions, timestamp, and influencer follower count. The dataset is notable for its subset of 9.7M-post Instagram influencer dataset covering the beauty category, with rich per-post engagement signals and influencer-level metadata. Intended for research into influencer marketing analysis, engagement prediction, social media content analysis, and sponsorship detection. This package holds the post metadata (one JSON .info file per post) and influencer lists; the post images, which the authors distribute separately on request, are not included.

436.8K records2020

Stack Exchange — judaism.stackexchange.com Analyzed

A Stack Exchange (judaism.stackexchange.com) dataset of 6,537 users, 31,649 answer-collaboration edges, 40,878 questions, 60,873 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 judaism.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..

434.7K records6.5K nodes31.6K edges2025

Stack Exchange — gamedev.stackexchange.com Analyzed

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..

432.7K records30K nodes65.2K edges2025

YouTube Snapshot 0502 Analyzed

A YouTube dataset of 39,147 videos, 762,840 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0502 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

430.6K records430.6K nodes762.8K edges2008

YouTube Snapshot 080707 Analyzed

A YouTube dataset of 62,978 videos, 774,403 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080707 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

427.2K records427.2K nodes774.4K edges2008

YouTube Snapshot 080701 Analyzed

A YouTube dataset of 61,977 videos, 755,227 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080701 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

425.7K records425.7K nodes755.2K edges2008

Voat — v/theawakening Analyzed

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.

424.1K records11.4K nodes130.9K edges2022

YouTube Snapshot 0315 Analyzed

A YouTube dataset of 45,268 videos, 838,482 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0315 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

401.3K records401.3K nodes838.5K edges2008

NFL Draft Reddit Comments Dataset Analyzed

A Reddit dataset of 398,487 comments from NFL subreddits during the 2020 draft, collected by Caio Brighenti via Reddit API (PRAW). Each record contains comment body, team, timestamp, VADER sentiment score, author. A real-time snapshot of NFL fan sentiment during the 2020 draft, capturing reactions to each pick across team subreddits. Suitable for sentiment analysis, sports analytics, social media analysis, fan behavior, natural language processing.

398.5K records2020

Pushshift Reddit — 2008-08 Analyzed

A Reddit (Pushshift archive, 2008-08) dataset of 397,916 comments and 174,362 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 583 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-08 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 583 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.

397.9K records229.3K nodes174.4K edges2020

YouTube Snapshot 0320 Analyzed

A YouTube dataset of 45,176 videos, 830,991 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0320 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

396.3K records396.3K nodes831K edges2008

YouTube Snapshot 0316 Analyzed

A YouTube dataset of 42,503 videos, 785,781 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 0316 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

392.4K records392.4K nodes785.8K edges2008

Pushshift Reddit — 2008-07 Analyzed

A Reddit (Pushshift archive, 2008-07) dataset of 390,922 comments and 172,692 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 548 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-07 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 548 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.

390.9K records226.5K nodes172.7K edges2020

YouTube Snapshot 080623 Analyzed

A YouTube dataset of 59,058 videos, 703,002 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080623 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

388.3K records388.3K nodes703K edges2008

YouTube Snapshot 080621 Analyzed

A YouTube dataset of 55,428 videos, 710,335 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080621 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

388K records388K nodes710.3K edges2008

Pushshift Reddit — 2008-06 Analyzed

A Reddit (Pushshift archive, 2008-06) dataset of 387,630 comments and 173,588 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains comment tree graph (nodes=comments, edges=reply relationships), 431 subreddits, node attributes: author, subreddit, score. Monthly slice of the Pushshift Reddit corpus for 2008-06 — comment tree graph showing reply structure, full comment text, and per-comment engagement metrics across 431 subreddits.. Suitable for Reddit comment tree analysis, reply network structure, community detection, sentiment analysis, engagement research, longitudinal Reddit growth studies.

387.6K records226.7K nodes173.6K edges2020

YouTube Snapshot 080703 Analyzed

A YouTube dataset of 58,063 videos, 675,259 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080703 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

386.4K records386.4K nodes675.3K edges2008

YouTube Snapshot 080727 Analyzed

A YouTube dataset of 60,152 videos, 710,000 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080727 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

385.6K records385.6K nodes710K edges2008

Stack Exchange — money.stackexchange.com Analyzed

A Stack Exchange (money.stackexchange.com) dataset of 24,820 users, 59,888 answer-collaboration edges, 38,860 questions, 72,475 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 money.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..

380.7K records24.8K nodes59.9K edges2025

YouTube Snapshot 080709 Analyzed

A YouTube dataset of 54,906 videos, 683,286 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080709 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

379.1K records379.1K nodes683.3K edges2008

YouTube Snapshot 080625 Analyzed

A YouTube dataset of 53,165 videos, 645,238 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080625 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

377K records377K nodes645.2K edges2008

Voat — v/pizzagate Analyzed

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.

374.7K records16.5K nodes152.1K edges2022

YouTube Snapshot 080723 Analyzed

A YouTube dataset of 50,216 videos, 623,801 related-video edges, collected by Cheng et al. via YouTube API (2007-2008). Each record contains video metadata (ID, uploader, age, category, length, views, rate, ratings, comments), related video IDs. Early YouTube snapshot 080723 capturing the video graph and metadata from the platform's rapid growth period in 2007-2008. Suitable for social network analysis, video recommendation, information diffusion, community detection.

372.1K records372.1K nodes623.8K edges2008

TBBT: r/consumeproduct Ban Intervention (2020) Analyzed

A Reddit (r/consumeproduct ban intervention, 2020) dataset of 26,786 pre-ban posts from banned community, 207,087 pre-ban control posts, 138,251 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/consumeproduct: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2020 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.

372.1K records10K nodes41.2K edges2026

iDRAMA-Scored: c/Funny Analyzed

A Scored.co (c/Funny) dataset of 65,066 submissions and 306,015 comments from 2,015 unique authors in c/Funny (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/Funny on Scored.co — General humor community. 371,081 total posts from 2,015 authors over 4 years. Suitable for deplatforming research, community behavior analysis, alternative platform discourse, content moderation effects, longitudinal community evolution.

371.1K records2K nodes2K edges2024

Fox8-23 AI-Powered Social Bot Dataset (ACM Web 2024) Analyzed

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..

368K records2024