2025

218 datasets tagged as the year “2025”.

218 datasets — page 4 of 5.

Stack Exchange — portuguese.stackexchange.com Analyzed

A Stack Exchange (portuguese.stackexchange.com) dataset of 1,353 users, 2,956 answer-collaboration edges, 2,520 questions, 4,400 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 portuguese.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..

27.6K records1.4K nodes3K edges2025

Stack Exchange — hardwarerecs.stackexchange.com Analyzed

A Stack Exchange (hardwarerecs.stackexchange.com) dataset of 2,641 users, 3,472 answer-collaboration edges, 4,354 questions, 4,064 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 hardwarerecs.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..

27.3K records2.6K nodes3.5K edges2025

Stack Exchange — computergraphics.stackexchange.com Analyzed

A Stack Exchange (computergraphics.stackexchange.com) dataset of 1,955 users, 3,120 answer-collaboration edges, 4,024 questions, 4,126 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 computergraphics.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..

26.7K records2K nodes3.1K edges2025

Stack Exchange — martialarts.stackexchange.com Analyzed

A Stack Exchange (martialarts.stackexchange.com) dataset of 2,074 users, 5,256 answer-collaboration edges, 2,307 questions, 6,874 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 martialarts.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..

26.6K records2.1K nodes5.3K edges2025

YikYak & Reddit Engagement Dataset Analyzed

A YikYak / Reddit dataset of 26,304 posts with engagement and controversy labels, collected by Riana Doctor via YikYak API and Reddit scraping (2025). Each record contains post text, vote total, comment count, controversy flag, timestamp, user alias, group ID. Dataset combining YikYak-style anonymous posts and Reddit content with explicit engagement and controversy annotations, enabling comparative analysis of controversial content across platforms. Suitable for controversy detection, engagement prediction, content moderation, sentiment analysis, social media dynamics.

26.3K records2025

Stack Exchange — substrate.stackexchange.com Analyzed

A Stack Exchange (substrate.stackexchange.com) dataset of 1,304 users, 3,681 answer-collaboration edges, 4,891 questions, 5,362 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 substrate.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..

25.1K records1.3K nodes3.7K edges2025

Stack Exchange — monero.stackexchange.com Analyzed

A Stack Exchange (monero.stackexchange.com) dataset of 2,096 users, 3,667 answer-collaboration edges, 4,460 questions, 5,352 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 monero.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..

24.4K records2.1K nodes3.7K edges2025

Stack Exchange — solana.stackexchange.com Analyzed

A Stack Exchange (solana.stackexchange.com) dataset of 2,107 users, 4,172 answer-collaboration edges, 4,695 questions, 5,285 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 solana.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..

22.4K records2.1K nodes4.2K edges2025

MADOC: Voat / gifs Analyzed

A MADOC (Voat, gifs) dataset of 5,022 users and 11,435 reply edges from 21,573 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.

21.6K records5K nodes11.4K edges2025

Stack Exchange — windowsphone.stackexchange.com Analyzed

A Stack Exchange (windowsphone.stackexchange.com) dataset of 2,452 users, 3,696 answer-collaboration edges, 3,441 questions, 4,586 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 windowsphone.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..

21.5K records2.5K nodes3.7K edges2025

Stack Exchange — cseducators.stackexchange.com Analyzed

A Stack Exchange (cseducators.stackexchange.com) dataset of 1,478 users, 3,504 answer-collaboration edges, 1,208 questions, 4,690 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 cseducators.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..

21.4K records1.5K nodes3.5K edges2025

MADOC: Voat / milliondollarextreme Analyzed

A MADOC (Voat, milliondollarextreme) dataset of 3,063 users and 10,819 reply edges from 21,190 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.

21.2K records3.1K nodes10.8K edges2025

Stack Exchange — sustainability.stackexchange.com Analyzed

A Stack Exchange (sustainability.stackexchange.com) dataset of 1,650 users, 3,428 answer-collaboration edges, 2,154 questions, 4,294 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 sustainability.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..

20.1K records1.6K nodes3.4K edges2025

Stack Exchange — stackapps.com Analyzed

A Stack Exchange (stackapps.com) dataset of 1,215 users, 1,783 answer-collaboration edges, 2,882 questions, 2,785 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 stackapps.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..

20.1K records1.2K nodes1.8K edges2025

Stack Exchange — crafts.stackexchange.com Analyzed

A Stack Exchange (crafts.stackexchange.com) dataset of 1,901 users, 3,367 answer-collaboration edges, 2,305 questions, 4,280 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 crafts.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..

19.2K records1.9K nodes3.4K edges2025

Stack Exchange — poker.stackexchange.com Analyzed

A Stack Exchange (poker.stackexchange.com) dataset of 1,839 users, 3,720 answer-collaboration edges, 2,151 questions, 4,597 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 poker.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..

18K records1.8K nodes3.7K edges2025

Stack Exchange — freelancing.stackexchange.com Analyzed

A Stack Exchange (freelancing.stackexchange.com) dataset of 2,229 users, 4,004 answer-collaboration edges, 2,017 questions, 4,750 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 freelancing.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..

16.5K records2.2K nodes4K edges2025

Stack Exchange — ukrainian.stackexchange.com Analyzed

A Stack Exchange (ukrainian.stackexchange.com) dataset of 645 users, 1,800 answer-collaboration edges, 2,238 questions, 3,361 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 ukrainian.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..

16.1K records645 nodes1.8K edges2025

Stack Exchange — iot.stackexchange.com Analyzed

A Stack Exchange (iot.stackexchange.com) dataset of 1,601 users, 2,223 answer-collaboration edges, 2,259 questions, 2,729 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 iot.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..

15.7K records1.6K nodes2.2K edges2025

Stack Exchange — cardano.stackexchange.com Analyzed

A Stack Exchange (cardano.stackexchange.com) dataset of 1,372 users, 3,045 answer-collaboration edges, 2,743 questions, 3,828 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 cardano.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..

14.9K records1.4K nodes3K edges2025

Stack Exchange — musicfans.stackexchange.com Analyzed

A Stack Exchange (musicfans.stackexchange.com) dataset of 2,069 users, 2,724 answer-collaboration edges, 2,276 questions, 3,440 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 musicfans.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..

14.3K records2.1K nodes2.7K edges2025

Stack Exchange — mythology.stackexchange.com Analyzed

A Stack Exchange (mythology.stackexchange.com) dataset of 1,222 users, 2,111 answer-collaboration edges, 2,038 questions, 3,064 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 mythology.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..

14.1K records1.2K nodes2.1K edges2025

Stack Exchange — esperanto.stackexchange.com Analyzed

A Stack Exchange (esperanto.stackexchange.com) dataset of 557 users, 2,124 answer-collaboration edges, 1,655 questions, 3,795 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 esperanto.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..

13K records557 nodes2.1K edges2025

Stack Exchange — korean.stackexchange.com Analyzed

A Stack Exchange (korean.stackexchange.com) dataset of 955 users, 2,001 answer-collaboration edges, 1,915 questions, 3,142 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 korean.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..

13K records955 nodes2K edges2025

Stack Exchange — eosio.stackexchange.com Analyzed

A Stack Exchange (eosio.stackexchange.com) dataset of 1,023 users, 2,134 answer-collaboration edges, 2,408 questions, 2,941 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 eosio.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..

12.5K records1K nodes2.1K edges2025

Stack Exchange — langdev.stackexchange.com Analyzed

A Stack Exchange (langdev.stackexchange.com) dataset of 413 users, 1,580 answer-collaboration edges, 728 questions, 2,259 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 langdev.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..

12.3K records413 nodes1.6K edges2025

Stack Exchange — tezos.stackexchange.com Analyzed

A Stack Exchange (tezos.stackexchange.com) dataset of 825 users, 1,728 answer-collaboration edges, 2,208 questions, 2,547 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 tezos.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..

11.5K records825 nodes1.7K edges2025

CLEF CheckThat! 2025 Task 2 — English Claim Normalization Analyzed

A CLEF CheckThat! 2025 Task 2 (english) dataset of 11,374 social media post and normalized claim pairs, collected by CLEF CheckThat! Lab organizers (2025). Each record contains social media post text containing a factual claim, normalized canonical claim statement. CLEF 2025 CheckThat! Task 2 (english) provides 11,374 pairs of social media posts and their normalized factual claims, enabling claim normalization and canonicalization research. Suitable for claim normalization, fact-checking automation, NLP text generation, multilingual claim extraction, social media fact verification.

11.4K records2025

Stack Exchange — coffee.stackexchange.com Analyzed

A Stack Exchange (coffee.stackexchange.com) dataset of 1,587 users, 2,509 answer-collaboration edges, 1,475 questions, 2,898 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 coffee.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..

11.1K records1.6K nodes2.5K edges2025

Stack Exchange — languagelearning.stackexchange.com Analyzed

A Stack Exchange (languagelearning.stackexchange.com) dataset of 1,009 users, 1,650 answer-collaboration edges, 1,396 questions, 2,140 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 languagelearning.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..

10.2K records1K nodes1.6K edges2025

Stack Exchange — ebooks.stackexchange.com Analyzed

A Stack Exchange (ebooks.stackexchange.com) dataset of 1,375 users, 1,813 answer-collaboration edges, 1,535 questions, 2,333 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 ebooks.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..

9.7K records1.4K nodes1.8K edges2025

Stack Exchange — beer.stackexchange.com Analyzed

A Stack Exchange (beer.stackexchange.com) dataset of 1,265 users, 2,182 answer-collaboration edges, 1,173 questions, 2,580 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 beer.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..

9.2K records1.3K nodes2.2K edges2025

Stack Exchange — proofassistants.stackexchange.com Analyzed

A Stack Exchange (proofassistants.stackexchange.com) dataset of 447 users, 993 answer-collaboration edges, 942 questions, 1,303 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 proofassistants.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..

9K records447 nodes993 edges2025

MADOC: Voat / KotakuInAction Analyzed

A MADOC (Voat, KotakuInAction) dataset of 1,878 users and 3,854 reply edges from 7,853 interactions, collected by Dankulov et al. via platform APIs, published at ICWSM 2025. Each record contains user-user reply edges, post and comment text, per-record sentiment scores (VADER and TextBlob), subjectivity scores, and toxicity scores (ToxiGen). The dataset is notable for its FAIR-compliant dataset with pre-computed NLP quality labels (sentiment, subjectivity, toxicity) per record, enabling network analysis and content quality research without additional annotation. Intended for research into social network analysis, toxicity detection, cross-platform community dynamics, misinformation research, and hate speech propagation studies.

7.9K records1.9K nodes3.9K edges2025

Stack Exchange — stellar.stackexchange.com Analyzed

A Stack Exchange (stellar.stackexchange.com) dataset of 850 users, 1,331 answer-collaboration edges, 1,463 questions, 1,674 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 stellar.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..

6.9K records850 nodes1.3K edges2025

Stack Exchange — vegetarianism.stackexchange.com Analyzed

A Stack Exchange (vegetarianism.stackexchange.com) dataset of 548 users, 1,147 answer-collaboration edges, 760 questions, 1,497 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 vegetarianism.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..

6.4K records548 nodes1.1K edges2025

Stack Exchange — drones.stackexchange.com Analyzed

A Stack Exchange (drones.stackexchange.com) dataset of 502 users, 848 answer-collaboration edges, 908 questions, 1,277 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 drones.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..

6.1K records502 nodes848 edges2025

Stack Exchange — iota.stackexchange.com Analyzed

A Stack Exchange (iota.stackexchange.com) dataset of 545 users, 936 answer-collaboration edges, 1,074 questions, 1,283 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 iota.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..

6.1K records545 nodes936 edges2025

Stack Exchange — conlang.stackexchange.com Analyzed

A Stack Exchange (conlang.stackexchange.com) dataset of 374 users, 825 answer-collaboration edges, 603 questions, 1,184 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 conlang.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..

5.3K records374 nodes825 edges2025

Stack Exchange — moderators.stackexchange.com Analyzed

A Stack Exchange (moderators.stackexchange.com) dataset of 540 users, 1,030 answer-collaboration edges, 582 questions, 1,296 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 moderators.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..

4.5K records540 nodes1K edges2025

Stack Exchange — bioacoustics.stackexchange.com Analyzed

A Stack Exchange (bioacoustics.stackexchange.com) dataset of 305 users, 798 answer-collaboration edges, 480 questions, 1,074 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 bioacoustics.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..

3.8K records305 nodes798 edges2025

MADOC: Voat / MensRights Analyzed

A MADOC (Voat, MensRights) dataset of 992 users and 1,628 reply edges from 3,735 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.

3.7K records992 nodes1.6K edges2025

HOT Speech: Hateful, Offensive, Toxic Speech Dataset Analyzed

A HOT Speech (hate/offensive/toxic speech dataset) dataset of 3,481 social media comments with multi-dimensional annotations, collected by SOMAR / ICPSR via Twitter, YouTube, and Reddit APIs (August 2021). Each record contains comment text, hard and soft labels (hateful, offensive, toxic), composite scores, and 21 researcher codes. multi-platform dataset with rich annotations including both MTurk worker labels and researcher codes. Suitable for hate speech detection, offensive language identification, toxicity classification, and political discourse analysis.

3.5K records2023

CLEF CheckThat! 2025 Task 2 — Spanish Claim Normalization Analyzed

A CLEF CheckThat! 2025 Task 2 (spanish) dataset of 3,458 social media post and normalized claim pairs, collected by CLEF CheckThat! Lab organizers (2025). Each record contains social media post text containing a factual claim, normalized canonical claim statement. CLEF 2025 CheckThat! Task 2 (spanish) provides 3,458 pairs of social media posts and their normalized factual claims, enabling claim normalization and canonicalization research. Suitable for claim normalization, fact-checking automation, NLP text generation, multilingual claim extraction, social media fact verification.

3.5K records2025

MADOC: Voat / CringeAnarchy Analyzed

A MADOC (Voat, CringeAnarchy) dataset of 876 users and 1,740 reply edges from 3,030 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.

3K records876 nodes1.7K edges2025

CLEF CheckThat! 2025 Subjectivity — Arabic Analyzed

A CLEF CheckThat! 2025 subjectivity task (arabic) dataset of 2,446 sentences with subjectivity labels (43.1% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (arabic) provides 2,446 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

2.4K records2025

CLEF CheckThat! 2025 Task 2 — Portuguese Claim Normalization Analyzed

A CLEF CheckThat! 2025 Task 2 (portuguese) dataset of 1,735 social media post and normalized claim pairs, collected by CLEF CheckThat! Lab organizers (2025). Each record contains social media post text containing a factual claim, normalized canonical claim statement. CLEF 2025 CheckThat! Task 2 (portuguese) provides 1,735 pairs of social media posts and their normalized factual claims, enabling claim normalization and canonicalization research. Suitable for claim normalization, fact-checking automation, NLP text generation, multilingual claim extraction, social media fact verification.

1.7K records2025

Stack Exchange — genai.stackexchange.com Analyzed

A Stack Exchange (genai.stackexchange.com) dataset of 192 users, 241 answer-collaboration edges, 268 questions, 320 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 genai.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..

1.6K records192 nodes241 edges2025

CLEF CheckThat! 2025 Subjectivity — Italian Analyzed

A CLEF CheckThat! 2025 subjectivity task (italian) dataset of 1,613 sentences with subjectivity labels (23.7% subjective), collected by CLEF CheckThat! Lab organizers (2025). Each record contains sentence text, binary subjectivity label (SUBJ/OBJ), sentence ID, conflict resolution flag. CLEF 2025 CheckThat! subjectivity (italian) provides 1,613 news sentences annotated for subjectivity — whether the sentence expresses opinions (SUBJ) or facts (OBJ). Suitable for subjectivity detection, opinion mining, NLP classification, news objectivity analysis, multilingual text classification.

1.6K records2025