A Twitter dataset of 1,412 tweets, collected by Olteanu et al. via Twitter API during the 2012 Costa Rica earthquake crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Costa Rica 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 Fediverse (misskey, active_user graph) dataset of 1,274 nodes, 19,491 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed, weighted edges based on user follow activity across instances, aggregated over time. The dataset is notable for its influence-weighted graph where nodes are instances and directed edges represent user following behavior (weighted by count), showing which servers generate content consumed by users on other servers. Intended for research into information flow analysis, influence measurement, content source tracking, and cross-instance user attention studies.
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 1,237 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 1,201 tweets from italy_earthquake_aug_2016, collected by Alam et al. for italy_earthquake_aug_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the italy_earthquake_aug_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,200 tweets, collected by Olteanu et al. via Twitter API during the 2012 Colorado wildfires crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Colorado wildfires 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 1,199 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 CLEF CheckThat! 2025 Task 2 (french) dataset of 1,174 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 (french) provides 1,174 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.
A Fediverse (pleroma, federation graph) dataset of 1,170 nodes, 185,908 edges (61 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
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 CLEF CheckThat! 2025 Task 2 (hindi) dataset of 1,081 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 (hindi) provides 1,081 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.
A Twitter dataset of 1,050 tweets, collected by Olteanu et al. via Twitter API during the 2012 Guatemala earthquake crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Guatemala 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 1,048 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 1,032 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 2012 Italy earthquakes crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Italy earthquakes 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 2012 Philipinnes floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Philipinnes 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 2012 Typhoon Pablo crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Typhoon Pablo 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 2012 Venezuela refinery crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2012 Venezuela refinery 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 Alberta floods crisis. Each record contains tweet text, crisis type, country, event name. The dataset is notable for its tweets from the 2013 Alberta 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 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 1,000 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 1,000 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 1,000 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 1,000 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 CLEF CheckThat! 2024 shared task (dutch) dataset of 995 sentences with binary check-worthiness labels (40.7% check-worthy), collected by CLEF CheckThat! Lab organizers (2024). Each record contains sentence text, binary check-worthiness label (Yes/No), sentence ID, source document. CLEF 2024 CheckThat! Task 1 (dutch) provides 995 sentences from political debates and social media annotated for check-worthiness — whether the claim merits fact-checking. Suitable for check-worthiness detection, fact-checking automation, misinformation research, NLP classification benchmarks, political discourse analysis.
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 Fediverse (pleroma, active_user graph) dataset of 821 nodes, 1,801 edges (24 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed, weighted edges based on user follow activity across instances, aggregated over time. The dataset is notable for its influence-weighted graph where nodes are instances and directed edges represent user following behavior (weighted by count), showing which servers generate content consumed by users on other servers. Intended for research into information flow analysis, influence measurement, content source tracking, and cross-instance user attention studies.
A Fediverse (lemmy, federation graph) dataset of 779 nodes, 166,096 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
A Fediverse (lemmy, federation_with_blocks graph) dataset of 779 nodes, 289,473 edges (62 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains directed edges with signs (+ for federation, - for blocks) between instances. The dataset is notable for its directed graph with both positive (federation) and negative (block) edges, showing communication relationships alongside active blocking between instances. Intended for research into defederation studies, conflict resolution, trust and distrust analysis in decentralized networks.
A Twitter dataset of 742 tweets from maryland_floods_2018, collected by Alam et al. for maryland_floods_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the maryland_floods_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Fediverse (friendica, federation graph) dataset of 594 nodes, 70,812 edges (59 snapshots merged), collected by Damie & Cyffers via weekly crawls over 6 months. Each record contains undirected edges between instances that have ever communicated, with instances.csv providing node metadata. The dataset is notable for its communication backbone graph where nodes are instances and edges represent any past interaction (undirected), showing how servers in the Fediverse are connected at the infrastructure level. Intended for research into decentralized network topology analysis, infrastructure resilience, cross-instance communication patterns, and federation policy impact studies.
Twitter (X)
Fediverse