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.
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.
The citation network of the arXiv High Energy Physics – Phenomenology (hep-ph) section, from SNAP (the KDD Cup 2003 data), as distributed by KONECT (cit-HepPh): 421,578 citations among 34,546 papers posted between January 1993 and April 2003. An edge points from a citing paper to the paper it cites. Useful for citation analysis, scientific impact and the growth of networks over time.
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 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.
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.
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.
A Twitter (MLK Day 2013) dataset of 327,707 users, 396,671 multiplex edges (retweets, mentions, replies), collected by D. R. G. and D. M.. Each record contains source, target, weight, layer (1=retweet, 2=mention, 3=reply). Multiplex Twitter network during MLK Day 2013 with three interaction layers. Suitable for multiplex network analysis, event dynamics, information propagation.
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.
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.
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.
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.
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.
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.
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.
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.
A CiteSeer digital library dataset of 384,413 nodes and 1,751,463 edges, collected by KONECT via CiteSeer database. Each record contains directed: True, weighted: False. Large directed citation network from the CiteSeer digital library — widely used in graph learning research.. Suitable for citation network analysis, graph neural networks benchmark, community detection.
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..
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.
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.
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 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.
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.
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.
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 Stack Exchange (android.stackexchange.com) dataset of 43,076 users, 56,924 answer-collaboration edges, 58,621 questions, 68,916 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 android.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A 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.
A Reddit (Pushshift archive, 2008-05) dataset of 218,148 comments and 167,545 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 287 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-05 — full comment text, reply graph, and engagement metrics across 287 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A Stack Exchange (puzzling.stackexchange.com) dataset of 13,533 users, 47,181 answer-collaboration edges, 27,362 questions, 63,997 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 puzzling.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A YouTube dataset of 41,835 videos, 784,710 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 0306 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.
A YouTube dataset of 52,130 videos, 640,597 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 080629 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.
A Twitter (NY Climate March 2014) dataset of 102,439 users, 353,495 multiplex edges (retweets, mentions, replies), collected by D. R. G. and D. M.. Each record contains source, target, weight, layer (1=retweet, 2=mention, 3=reply). Multiplex Twitter network during NY Climate March 2014 with three interaction layers. Suitable for multiplex network analysis, event dynamics, information propagation.
A YouTube dataset of 54,024 videos, 602,777 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 080715 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.
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.
A Stack Exchange (cs.stackexchange.com) dataset of 24,745 users, 45,645 answer-collaboration edges, 48,390 questions, 56,255 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 cs.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Instagram (interior influencers) dataset of 348,559 posts from interior 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 interior 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.
A YouTube dataset of 51,513 videos, 622,451 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 080705 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.
A Twitter dataset of 346,573 nodes, 1,091,552 edges, collected by Shao et al. via Hoaxy API (OSoMe/Indiana University). Each record contains from_user_id, to_user_id, tweet_id, tweet_created_at, site_type (claim/fact-checking). Retweet diffusion network of misinformation and fact-checking content surrounding the 2016 US election; distinguishes claim vs. fact-checking retweets.. Suitable for Misinformation diffusion, fact-checking network analysis, network epidemiology..
A YouTube dataset of 48,705 videos, 584,997 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 080713 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.
A Reddit (r/darkhumorandmemes ban intervention, 2020) dataset of 15,594 pre-ban posts from banned community, 185,567 pre-ban control posts, 139,739 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/darkhumorandmemes: 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.
A YouTube dataset of 46,826 videos, 565,222 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 080721 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.
A Amazon (co-purchasing network) dataset of 334,863 nodes and 925,872 edges, collected by Yang & Leskovec from Amazon website (2012). Each record contains product-product co-purchasing edges and product-category communities. The dataset is notable for its product co-purchasing network with ground-truth communities from categories. Intended for research into community detection, recommendation systems, and product relationship analysis.
A YouTube dataset of 48,842 videos, 570,756 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 080717 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.
A Stack Exchange (chemistry.stackexchange.com) dataset of 21,197 users, 43,218 answer-collaboration edges, 44,825 questions, 52,010 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 chemistry.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A 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.
A Scored.co (c/NoNewNormal) dataset of 30,770 submissions and 291,530 comments from 3,101 unique authors in c/NoNewNormal (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/NoNewNormal on Scored.co — Anti-lockdown / COVID skepticism community. 322,300 total posts from 3,101 authors over 4 years. Suitable for deplatforming research, community behavior analysis, alternative platform discourse, content moderation effects, longitudinal community evolution.
A Stack Exchange (ux.stackexchange.com) dataset of 25,246 users, 76,178 answer-collaboration edges, 32,718 questions, 84,000 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 ux.stackexchange.com — directed weighted graph where edges represent knowledge-sharing relationships (A answered B's question), with edge weight reflecting answer quality. Enables prestige hierarchy, community detection, and expertise flow analysis.. Suitable for expertise network analysis, reputation systems, community detection, knowledge flow, PageRank-based authority ranking, Q&A platform dynamics..
A Instagram (fitness influencers) dataset of 319,414 posts from fitness 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 fitness 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.
A Reddit (Pushshift archive, 2008-03) dataset of 187,499 comments and 143,043 reply edges, collected by Jason Baumgartner via Pushshift.io Reddit API archive. Each record contains directed reply graph, 259 subreddits, content metrics: score, controversiality, gilded. Monthly slice of the Pushshift Reddit corpus for 2008-03 — full comment text, reply graph, and engagement metrics across 259 subreddits.. Suitable for longitudinal Reddit analysis, reply network structure, community detection, sentiment analysis, engagement research.
A DBLP (co-authorship network) dataset of 317,080 nodes and 1,049,866 edges, collected by Yang & Leskovec from DBLP bibliography (2012). Each record contains author-author co-authorship edges and publication-venue communities. The dataset is notable for its academic collaboration network with ground-truth communities from publication venues. Intended for research into community detection, network evolution, and scientific collaboration analysis.
YouTube
Voat
Twitter (X)
Reddit
Stack Exchange
Scored
Instagram
Amazon