A Twitter dataset of 1,199 tweets, collected by Olteanu et al. via Twitter API during the 2013 Australia bushfire crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Australia bushfire crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Bohol earthquake crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Bohol earthquake crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Boston bombings crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Boston bombings crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Brazil nightclub fire crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Brazil nightclub fire crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Colorado floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Colorado floods crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,100 tweets, collected by Olteanu et al. via Twitter API during the 2013 Glasgow helicopter crash crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Glasgow helicopter crash crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,032 tweets, collected by Olteanu et al. via Twitter API during the 2013 LA airport shootings crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 LA airport shootings crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Lac Megantic train crash crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Lac Megantic train crash crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Manila floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Manila floods crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 NY train crash crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 NY train crash crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,200 tweets, collected by Olteanu et al. via Twitter API during the 2013 Queensland floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Queensland floods crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,442 tweets, collected by Olteanu et al. via Twitter API during the 2013 Russia meteor crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Russia meteor crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Sardinia floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Sardinia floods crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,250 tweets, collected by Olteanu et al. via Twitter API during the 2013 Savar building collapse crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Savar building collapse crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Singapore haze crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Singapore haze crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 Spain train crash crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Spain train crash crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,048 tweets, collected by Olteanu et al. via Twitter API during the 2013 Typhoon Yolanda crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Typhoon Yolanda crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 1,000 tweets, collected by Olteanu et al. via Twitter API during the 2013 West Texas explosion crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 West Texas explosion crisis, collected systematically across 26 events for comparative analysis. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness.
A Twitter dataset of 27,933 tweets across 26 crisis events (2012-2013), collected by Olteanu et al. via Twitter API during 26 crisis events. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its Systematically collected dataset of 26 crisis events with balanced sampling across event types, enabling comparative analysis of social media communications across different crises. Cumulative version combines all events into a single corpus.. Intended for research into crisis informatics, disaster response, social media analysis, cross-crisis comparison, emergency communication patterns, situation awareness, multi-event NLP benchmarking.
A Twitter dataset of 1,486 tweets referencing 1,590 images by URL, collected by Alam et al. for the California Wildfires 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the California Wildfires 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 3,992 tweets referencing 4,569 images by URL, collected by Alam et al. for the Hurricane Harvey 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Harvey 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 4,021 tweets referencing 3,611 images by URL, collected by Alam et al. for the Hurricane Irma 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Irma 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 3,995 tweets referencing 4,691 images by URL, collected by Alam et al. for the Hurricane Maria 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Hurricane Maria 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 496 tweets referencing 597 images by URL, collected by Alam et al. for the Iraq-Iran Earthquake 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Iraq-Iran Earthquake 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 1,237 tweets referencing 1,380 images by URL, collected by Alam et al. for the Mexico Earthquake 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Mexico Earthquake 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 830 tweets referencing 1,027 images by URL, collected by Alam et al. for the Southeast Asia Floods 2017 crisis. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its multimodal dataset from the Southeast Asia Floods 2017 crisis, collected from Twitter during the event with full Twitter API metadata. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A Twitter dataset of 16,057 tweets across 7 crisis events referencing 17,465 images by URL, collected by Alam et al. for 7 major natural disasters in 2017. Each record contains tweet text, engagement metrics (retweets, favorites, replies, quotes), user metadata, media attachments, crisis code. The dataset is notable for its Systematically collected multimodal dataset of 7 natural disasters with full Twitter API metadata. Cumulative version combines all events into a single corpus. Intended for research into crisis informatics, multimodal learning, disaster response, image classification, tweet filtering, cross-event engagement analysis. This copy (the SocialED redistribution) holds the tweet objects only: the images are referenced by URL and the image files are not included, and neither are CrisisMMD's human annotations (informativeness, humanitarian category, damage severity).
A DBLP Computer Science Bibliography dataset of 5,425,963 nodes and 8,649,016 edges, collected by KONECT via DBLP database. Each record contains directed: False, weighted: False. Large bipartite network linking 1.4M authors to 4M papers in DBLP — one of the largest academic bipartite networks available.. Suitable for academic collaboration analysis, authorship networks, bipartite graph research.
A DBLP Computer Science Bibliography dataset of 12,591 nodes and 49,743 edges, collected by KONECT via DBLP database. Each record contains directed: True, weighted: False. Directed citation network of computer science papers in the DBLP bibliography.. Suitable for citation network analysis, academic influence, community detection.
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.
A DBpedia (structured Wikipedia knowledge base) dataset of 18,268,991 nodes and 136,537,566 edges, collected by DBpedia community via Wikipedia extraction. Each record contains directed: True, weighted: True. Large-scale RDF knowledge graph extracted from Wikipedia — multiple relation types (starring, genre, occupation, team, etc.) across millions of entities.. Suitable for knowledge graph completion, entity linking, semantic web research.
A DBTropes (structured TV Tropes database) dataset of 152,093 nodes and 3,232,134 edges, collected by M. Kiesel et al. via TV Tropes crawl. Each record contains directed: False, weighted: False. Bipartite network of films and narrative tropes they contain from DBTropes — useful for computational narrative analysis.. Suitable for computational narrative analysis, bipartite network analysis, film studies.
A Delicious (social bookmarking) dataset of 536,408 users and 1,366,663 friendship edges, collected by Aneeth Anand via Delicious crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from the Delicious social bookmarking service, where users stored, shared, and discovered web bookmarks. Intended for research into social network analysis, community detection, information sharing behavior, and social bookmarking platform structure studies.
A Delicious social bookmarking platform (tag-item network) dataset of 38,289,740 nodes and 137,240,382 edges, collected by KONECT via Delicious API. Each record contains directed: False, weighted: True, temporal: True. Massive temporal bipartite network of Delicious tags and bookmarked items — 301M edges across 38M tags and items with Unix timestamps.. Suitable for social tagging analysis, folksonomy research, tag-item recommendation.
A Delicious social bookmarking platform (user-item network) dataset of 34,611,302 nodes and 101,798,957 edges, collected by KONECT via Delicious API. Each record contains directed: False, weighted: True, temporal: True. Massive temporal bipartite network of Delicious users and bookmarked URLs — 301M edges across 35M users and items with Unix timestamps.. Suitable for social bookmarking analysis, recommendation systems, large-scale bipartite networks.
A Delicious social bookmarking platform (user-tag network) dataset of 5,345,180 nodes and 81,989,133 edges, collected by KONECT via Delicious API. Each record contains directed: False, weighted: True, temporal: True. Massive temporal bipartite network of Delicious users and tags they used — 301M edges across 5.3M users and tags with Unix timestamps.. Suitable for social tagging analysis, folksonomy research, large-scale bipartite networks.
A Digg (social news) dataset of 771,231 users and 5,911,205 friendship edges, collected by Mithila Nagendra via Digg crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from the pre-v4 Digg social news platform, where users voted stories up (digging) or down (burying). Intended for research into social network analysis, community detection, information diffusion, and social news platform structure studies.
A Twitter dataset of 263,555 tweets with binary event labels (14,129 disruptive events, 248,499 non-events) related to Bitcoin and cryptocurrency markets, collected by Mehta et al. via Twitter API, 2021. Each record contains tweet text, binary event/non-event label, follower count, location, username, Bitcoin price at time of tweet, and retweet count. one of few datasets explicitly linking social media content to financial market disruption events, with synchronized Bitcoin price data enabling direct study of social signal → market movement relationships. Suitable for event detection, financial market prediction from social media, cryptocurrency sentiment analysis, and disruptive event classification.
A Discogs music marketplace and database dataset of 270,786 nodes and 481,661 edges, collected by KONECT via Discogs database. Each record contains directed: False, weighted: True, temporal: False. Bipartite network linking Discogs users to music genres they collect — 4.1M edges across 270k users and 15 genres.. Suitable for recommender systems, music preference analysis, bipartite network analysis.
A Democratic National Committee (email communications, 2016) dataset of 906 nodes and 10,429 edges, collected by WikiLeaks DNC email leak. Each record contains directed: False, weighted: True, signed: False, temporal: False. Weighted undirected co-recipient network from the leaked DNC emails — two people are connected if they appeared together on email threads, with edge weights indicating co-occurrence frequency.. Suitable for political network analysis, email network analysis, community detection.
A Bottlenose dolphin community (Doubtful Sound, New Zealand) dataset of 62 nodes and 159 edges, collected by D. Lusseau et al.. Each record contains directed: False, weighted: False, signed: False. Classic benchmark: 62 bottlenose dolphins with frequent associations — widely used to validate community detection algorithms.. Suitable for community detection benchmark, animal social network analysis.
A Douban (Chinese social network) dataset of 154,908 users and 327,162 friendship edges, collected by Long Qiu via Douban crawl (December 2010). Each record contains user-user friendship edges and user IDs. The dataset is notable for its friendship network from Douban, China's largest online community for book, movie, and music reviews and recommendations. Intended for research into social network analysis, community detection, Chinese social media research, and content-sharing platform structure studies.
A Edinburgh Associative Thesaurus (word association study) dataset of 23,132 nodes and 312,310 edges, collected by G.R. Kiss et al.. Each record contains directed: True, weighted: True. Directed word association network from the Edinburgh Associative Thesaurus — edges connect stimulus words to response words.. Suitable for semantic network analysis, word association modeling, NLP.
A TikTok (pro-eating disorder content) dataset of 85 videos and photo posts annotated using the EDE clinical framework, collected by Shaveet, Viranda, and Choudhury at Cornell University. Each record contains content type (video/photos), human-written content summary, EDE subscale and diagnostic item annotations, visual and audio element labels, audio tempo/valence/arousal scores, harmonic ratio, and mode. EDTT is the first clinically-grounded dataset of pro-eating-disorder TikTok content, with 47 videos and 38 photo posts annotated using the Eating Disorder Examination framework by Cornell researchers. Suitable for eating disorder content detection, harmful content moderation, multimodal annotation research, TikTok platform analysis, clinical NLP, audio-visual content analysis.
A Wikipedia (English edition, 2013 snapshot) dataset of 4,203,323 article nodes and 101,311,614 directed hyperlink edges, collected by Leskovec et al. via Wikipedia XML dump (SNAP, 2013). Each record contains source article ID, destination article ID (directed hyperlink). Complete English Wikipedia hyperlink graph from a 2013 snapshot — one of the largest hyperlink networks publicly available, capturing the full link structure of 4.2M Wikipedia articles.. Suitable for hyperlink network analysis, graph evolution studies, link prediction, Wikipedia structure research, large-scale directed graph algorithms.
A Enron dataset of 1,148,072 emails, collected by Network Repository. Each record contains email communication. Enron email network from the 1999-2002 period. Suitable for organizational communication, network analysis.
A Epinions.com (consumer review platform) dataset of 131,828 users and 841,372 directed signed edges (717,667 trust, 123,705 distrust), collected by Richardson et al. via Epinions.com crawl, distributed by SNAP. Each record contains directed signed edges between users: +1 indicates explicit trust, -1 indicates explicit distrust, capturing both positive and negative social relationships. one of the largest publicly available signed social networks, with explicit user-declared trust and distrust labels rather than inferred sentiment — making it ideal for signed graph algorithm benchmarking. Suitable for signed network analysis, trust propagation, link sign prediction, community detection in signed graphs, and balance theory validation.
A Escort review website (sex worker review community) dataset of 16,730 nodes and 39,044 edges, collected by Rocha et al. via web crawl. Each record contains directed: False, weighted: True, signed: True, temporal: True. Bipartite signed network of escort reviews: clients rate escorts +1 (positive), 0 (neutral), or -1 (negative), with Unix timestamps. One of the few large-scale signed bipartite networks available.. Suitable for signed network analysis, bipartite network analysis, trust propagation.
A European research institution internal email system dataset of 986 employees and 332,334 directed email interactions across 42 departments, collected by Leskovec et al. via SNAP (anonymized institutional email logs). Each record contains sender employee ID, recipient employee ID, Unix timestamp, and department label per employee (42 departments). Temporal directed email communication network from a European research institution with ground-truth department labels for all 986 employees — enabling evaluation of community detection algorithms against known organizational structure.. Suitable for community detection benchmarking, organizational network analysis, temporal email network analysis, higher-order graph clustering.
The international E-road network, a road network located mostly in Europe, compiled by Lovro Šubelj and Marko Bajec and distributed by KONECT (subelj_euroroad): 1,174 cities linked by 1,417 undirected roads, where an edge means two cities are joined by an E-road. City names are included. Useful for studying spatial and infrastructure networks, network robustness and community detection.