Synthetic, templated data: 75,000 short texts labelled with one of 6 harassment categories or non-toxic (10,714 or 10,715 each), with a 'platform' value (Facebook, Instagram, Reddit, news portal) and character offsets of the toxic span. The texts are generated from a small set of templates: the toxic rows use only 30 distinct toxic phrases, and every row ends in a '(Ref Node: #NNNNNN)' token. The platform values are assigned, not observed. Published on Mendeley Data. Suitable for testing span-tagging code, not for measuring real cyberbullying.
A Reddit (r/chapotraphouse ban intervention, 2020) dataset of 865,937 pre-ban posts from banned community, 1,272,364 pre-ban control posts, 1,279,975 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/chapotraphouse: 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 Reddit (r/chodi ban intervention, 2022) dataset of 43,547 pre-ban posts from banned community, 631,445 pre-ban control posts, 544,604 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/chodi: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2022 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
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 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 Reddit (r/darknetmarkets ban intervention, 2018) dataset of 32,712 pre-ban posts from banned community, 119,036 pre-ban control posts, 16,348 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/darknetmarkets: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/debatealtright ban intervention, 2020) dataset of 12,093 pre-ban posts from banned community, 53,216 pre-ban control posts, 33,548 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/debatealtright: 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 dataset from The Big Ban Theory (Cerulli et al., ICWSM 2026) on the June 2015 ban of r/fatpeoplehate: 111,751 posts in the subreddit in the three months before the ban, and 39,427 posts in v/fatpeoplehate on Voat, where the community moved, in the three months after it. Each record holds the post ID, text, pseudonymized author, community, score and time. Suitable for deplatforming research, community migration and pre/post intervention analysis.
A Reddit (r/gendercritical ban intervention, 2020) dataset of 40,976 pre-ban posts from banned community, 94,239 pre-ban control posts, 72,306 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/gendercritical: 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 Reddit (r/greatawakening ban intervention, 2018) dataset of 329,183 pre-ban posts from banned community, 690,552 pre-ban control posts, 620,307 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/greatawakening: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/gunsforsale ban intervention, 2018) dataset of 5,837 pre-ban posts from banned community, 33,758 pre-ban control posts, 5,222 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/gunsforsale: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/incels ban intervention, 2017) dataset of 273,009 pre-ban posts from banned community, 841,379 pre-ban control posts, 563,354 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/incels: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2017 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/milliondollarextreme ban intervention, 2018) dataset of 129,276 pre-ban posts from banned community, 536,408 pre-ban control posts, 401,687 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/milliondollarextreme: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/physical_removal ban intervention, 2017) dataset of 12,921 pre-ban posts from banned community, 370,492 pre-ban control posts, 222,245 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/physical_removal: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2017 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/sanctionedsuicide ban intervention, 2018) dataset of 27,002 pre-ban posts from banned community, 142,493 pre-ban control posts, 52,442 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/sanctionedsuicide: pre- and post-ban Reddit dataset from The Big Ban Theory — standardized 3-month window around the 2018 moderation intervention with matched control communities. Suitable for content moderation effects, community migration, deplatforming research, pre/post intervention analysis, Reddit ban studies.
A Reddit (r/shitneoconssay ban intervention, 2020) dataset of 4,592 pre-ban posts from banned community, 39,813 pre-ban control posts, 25,351 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/shitneoconssay: 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 Reddit (r/the_donald ban intervention, 2020) dataset of 221,682 pre-ban posts from banned community, 680,784 pre-ban control posts, 488,109 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/the_donald: 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 Terrorist Attacks dataset of 645 nodes, 3,172 edges, 6 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Terrorist Attacks network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A Terrorist Relations dataset of 881 nodes, 8,592 edges, 4 classes, collected by Yang et al. (ICML 2016). Each record contains node features, citation edges, class labels. Terrorist Relations network with bag-of-words features. Suitable for node classification, semi-supervised learning, graph neural networks.
A TextDetox 2024/2025 shared task (15 languages) dataset of 71,374 posts across 15 languages with binary toxicity labels, collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic), language. Combined multilingual toxicity benchmark covering 15 languages including low-resource languages (Amharic, Tatar, Hindglish) — 71,374 balanced samples total. Suitable for multilingual toxicity detection, cross-lingual transfer learning, low-resource NLP, content moderation benchmarking.
A TextDetox 2024 shared task (Amharic) dataset of 5,000 Amharic posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Amharic provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Arabic) dataset of 5,000 Arabic posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Arabic provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Chinese) dataset of 5,000 Chinese posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Chinese provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (English) dataset of 5,000 English posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox English provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (French) dataset of 5,000 French posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox French provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (German) dataset of 5,000 German posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox German provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Hebrew) dataset of 2,011 Hebrew posts (807 toxic, 1,204 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Hebrew provides 2,011 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Hindglish) dataset of 4,363 Hindglish posts (2,200 toxic, 2,163 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Hindglish provides 4,363 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Hindi) dataset of 5,000 Hindi posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Hindi provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Italian) dataset of 5,000 Italian posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Italian provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Japanese) dataset of 5,000 Japanese posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Japanese provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Russian) dataset of 5,000 Russian posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Russian provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Spanish) dataset of 5,000 Spanish posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Spanish provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Tatar) dataset of 5,000 Tatar posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Tatar provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A TextDetox 2024 shared task (Ukrainian) dataset of 5,000 Ukrainian posts (2,500 toxic, 2,500 non-toxic), collected by Dementieva et al. for PAN/CLEF TextDetox 2024. Each record contains post text, binary toxicity label (0=non-toxic, 1=toxic). TextDetox Ukrainian provides 5,000 balanced binary toxicity annotations — part of a 15-language multilingual benchmark for cross-lingual toxicity detection research. Suitable for toxicity detection, multilingual content moderation, cross-lingual NLP, hate speech classification, text detoxification.
A Twitter dataset of 25,327 nodes, 629,514 edges, collected by Shao et al. via Hoaxy + Botometer (OSoMe/Indiana University). Each record contains user centralities (betweenness, pagerank), bot scores, retweet graph, user-domain bipartite graph. Retweet network of low-credibility content with per-user bot scores; shows bots systematically amplify misinformation early in diffusion cascades.. Suitable for Bot-mediated misinformation diffusion, social bot impact measurement..
A TheMarker Cafe dataset of 69,413 users and 1,644,849 undirected friendship links, collected by Fire et al. (2011) and distributed by Network Repository. TheMarker Cafe was an Israeli online community where most interaction was in Hebrew. Suitable for link prediction, social network analysis, community detection and regional online community studies.
A TikTok dataset of 1,035,817 videos, 4,920 creators, 27,169,858 engagement records, collected by Lingbo et al.. Each record contains video_id, author_id, create_time, description, hashtags, music, daily engagement (plays, likes, comments, shares, collects). Large-scale TikTok dataset with video metadata and 30-day engagement trajectories. Suitable for engagement analysis, creator behavior, viral prediction, social media dynamics.
A TikTok dataset of 209,543 videos from 1,872 creators, collected by Lingbo et al.. Each record contains video_id, author_id, create_time, description, transcript, GPT summary, topic, emotion scores, music metadata. Large-scale TikTok dataset with video metadata, GPT-generated summaries, emotion scores, and 30-day engagement trajectories. Suitable for engagement analysis, creator behavior, viral prediction, social media dynamics.
A Twitch dataset of 1,000 top streamers with viewership and engagement metrics, collected by Aayush Mishra via Twitch API (2020). Each record contains channel name, watch time, streaming time, max/average viewers, followers, followers gained, views gained, partnership status, age-restriction status, and language. A comprehensive snapshot of the top 1,000 Twitch streamers, capturing key engagement and growth metrics for the platform's most influential content creators. Suitable for influencer analysis, engagement prediction, platform dynamics, streamer growth modeling, gaming community studies.
A Twitter dataset of 4,465 labeled Twitter accounts (991 bots, 3474 genuine), collected by Ashu273k — curated subset of Cresci et al. (2017). Each record contains user profile features (followers, friends, statuses, favourites, listed count), binary bot/genuine label, user bio text. Small, clean subset of the Cresci-2017 dataset curated for rapid prototyping and benchmarking of bot detection models, with pre-extracted user-level features and binary labels. Suitable for bot detection, social spambot classification, feature selection for account authenticity, rapid prototyping of detection algorithms.
A snapshot of Truth Social from February to September 2022, released by Patrick Gerard, Nicholas Botzer and Tim Weninger (University of Notre Dame) on Zenodo (7522646). 454,458 users and 845,060 posts ('truths'), with 4,002,115 follow edges, 506,276 replies and 10,508 quotes, plus hashtags, media and external URLs, as 13 tab-separated tables. Suitable for social network analysis, political communication and misinformation research on an alternative platform.
A Truth Social (user account corpus) dataset of 90,683 user accounts with 1,611 verified and 0 bot-labeled, collected by TruthStance project team via Truth Social API. Each record contains username, follower/following counts, account creation date, profile bio text, bot label, verified status. TruthStance covers 90,683 Truth Social accounts spanning 2022-02 to 2025-12, with 1,611 verified accounts and 61,226 users with bio text — one of few datasets focused on Truth Social platform users. Suitable for Truth Social platform analysis, bot detection, political social media research, user behavior modeling, alternative platform studies.
A TUAW (The Unofficial Apple Weblog) dataset of 10,485 blog posts, collected by Agarwal, Tang, Liu, and Yu via TUAW crawl (2004-2007). Each record contains blog post title, text, author, categories, publication date, inlinks, outlinks, and comment counts. The dataset is notable for its blog dataset with rich metadata, representing a closed community of Apple-focused bloggers. Intended for research into influential blogger identification, blog post analysis, text classification, and influence modeling.
A Twitter (#BlackLivesMatter) dataset of 9,165 tweets (3,084 hate speech, 6,081 non-hate), collected by Giorgi et al. via Twitter API (2020). Each record contains tweet text, binary hate label (0/1), hashtags, source platform, user friends/favourites count, retweet flag. 9,165 BLM-related tweets with hate speech labels — captures online discourse during the 2020 Black Lives Matter movement with 3,084 hate speech examples. Suitable for hate speech detection, social movement analysis, BLM discourse research, Twitter content moderation, political communication, racial justice NLP.
A Twitch (gaming social network) dataset of 168,116 users and 6,797,558 mutual follower edges, collected by Rozemberczki & Sarkar via Twitch public API (2018). Each record contains undirected mutual follower edges, node features (views, mature, life_time, created_at, updated_at, dead_account, language, affiliate). The dataset is notable for its large-scale strongly connected component with no missing attributes, designed for node classification and count data regression. Intended for research into social network analysis, node classification, community detection, and transfer learning in gaming communities.
A Twitter (2010 snapshot) dataset of 41,652,230 users and 1,468,365,182 directed follower edges, collected by Kwak, Lee, Park & Moon via Twitter API (2010). Each record contains source user ID, follower user ID (edge from i to j means j follows i). Complete snapshot of the Twitter follower graph from 2010 — one of the largest social network datasets ever released publicly, capturing the full follower structure of 41.6M Twitter users with 1.47 billion directed edges.. Suitable for large-scale social network analysis, community detection, influence propagation, graph algorithm benchmarking, Twitter network evolution studies.
The five Twitter multiplex event networks (Cannes 2013, MLK Day 2013, Moscow Athletics 2013, NY Climate March 2014, Obama in Israel 2013) side by side in one graph: 3,238,746 users and 5,175,900 weighted retweet, mention and reply edges. Each release numbers its users independently, so node IDs are event:user and no account is linked across events. Suitable for multiplex network analysis and comparing information spreading across events.
A Twitter dataset of 11,929 labeled financial tweets, collected by zeroshot via Twitter API. Each record contains tweet text, sentiment label (positive/negative/neutral), sentiment value (0/1/2), train/valid split. A labeled dataset of tweets about financial news, with sentiment annotations for stock market-related content. Suitable for sentiment analysis, financial NLP, stock market prediction, social media analytics, natural language processing.
A Twitter dataset of 456,631 users, 14,855,875 follow/mention edges, collected by De Domenico et al. (2013) via Twitter API around Higgs boson announcement (July 4, 2012). Each record contains directed edges between Twitter users representing follows or mentions, capturing information propagation during a major scientific announcement. Temporal network capturing information spreading around the Higgs boson discovery announcement, enabling study of scientific rumor propagation and information cascades in real-time social media. Suitable for information propagation, rumor dynamics, temporal network analysis, scientific communication studies, social media epidemiology.
Facebook
Instagram
Reddit
Twitter (X)
TheMarker
TikTok
Twitch
Truth Social