42 datasets tagged as the topic “Rumour”.
42 datasets.
A 4chan (/pol/) dataset of 4,998,945 posts from /pol/, collected by kjj0 via 4chan API. Each record contains post text content. A 5 million post sample from 4chan's /pol/ board, capturing political discourse, extremism, and online communities. Suitable for misinformation, propaganda, hate speech, political communication, online communities, extremist discourse.
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.
A Twitter dataset of 60,082 tweets across 6 crisis events (0 on-topic, 60,082 off-topic), collected by Olteanu et al. via crowdsourcing for 6 crisis events. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its Systematically collected dataset of 6 crisis events with crowdsourced on-topic/off-topic labels from at least 3 workers per tweet, enabling comparative analysis of tweet relevance across different crises. Cumulative version combines all events into a single corpus.. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness, multi-event NLP benchmarking.
Twitter conversations around the Charlie Hebdo shooting in Paris (January 2015), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 2,079 threads, each a source tweet and its replies, of which 458 were judged rumours by journalists and 1,621 not. Every rumour also carries its veracity as later established: 193 true, 116 false and 149 unverified. 38,268 tweets in all, with full tweet JSON. ECHO builds the reply network (36,189 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
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.
Twitter conversations around the Ferguson unrest after the shooting of Michael Brown (August 2014), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 1,143 threads, each a source tweet and its replies, of which 284 were judged rumours by journalists and 859 not. Every rumour also carries its veracity as later established: 10 true, 8 false and 266 unverified. 24,175 tweets in all, with full tweet JSON. ECHO builds the reply network (22,260 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
Twitter conversations around the Sydney Lindt café siege (December 2014), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 1,221 threads, each a source tweet and its replies, of which 522 were judged rumours by journalists and 699 not. Every rumour also carries its veracity as later established: 382 true, 86 false and 54 unverified. 23,996 tweets in all, with full tweet JSON. ECHO builds the reply network (22,775 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
Twitter conversations around the Ottawa Parliament Hill shooting (October 2014), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 890 threads, each a source tweet and its replies, of which 470 were judged rumours by journalists and 420 not. Every rumour also carries its veracity as later established: 329 true, 72 false and 69 unverified. 12,284 tweets in all, with full tweet JSON. ECHO builds the reply network (11,394 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
A Twitter dataset of 10,033 tweets (0 on-topic, 10,033 off-topic), collected by Olteanu et al. via crowdsourcing for the Queensland Floods 2013 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the Queensland Floods 2013 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 10,031 tweets (0 on-topic, 10,031 off-topic), collected by Olteanu et al. via crowdsourcing for the Alberta Floods 2013 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the Alberta Floods 2013 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 10,012 tweets (0 on-topic, 10,012 off-topic), collected by Olteanu et al. via crowdsourcing for the Boston Bombings 2013 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the Boston Bombings 2013 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 10,008 tweets (0 on-topic, 10,008 off-topic), collected by Olteanu et al. via crowdsourcing for the Sandy Hurricane 2012 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the Sandy Hurricane 2012 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 10,006 tweets (0 on-topic, 10,006 off-topic), collected by Olteanu et al. via crowdsourcing for the West Texas Explosion 2013 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the West Texas Explosion 2013 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 9,992 tweets (0 on-topic, 9,992 off-topic), collected by Olteanu et al. via crowdsourcing for the Oklahoma Tornado Season 2013 crisis. Each record contains tweet text, on-topic/off-topic label (crowdsourced majority voting), crisis type, country, year. The dataset is notable for its tweets from the Oklahoma Tornado Season 2013 crisis, labeled by crowdsourcing workers for on-topic/off-topic classification with majority voting from at least 3 workers per tweet. Intended for research into crisis informatics, tweet filtering, on-topic detection, information extraction, crowdsourcing evaluation, event detection, situation awareness.
A Twitter dataset of 4,952 tweets (1,238 rumour, 3,714 non-rumour) from the 2013 Boston Marathon bombings, collected by Zubiaga, Liakata, and Procter — Augmented PHEME (Zenodo, 2019). Each record contains tweet text, binary rumour/non-rumour label, timestamp, reaction thread structure linking source tweets to replies. Augmented extension of PHEME covering the Boston Marathon bombings event with both rumour threads and non-rumour threads, providing a balanced benchmark for rumour detection with reaction graph structure. Suitable for rumour detection, misinformation classification, crisis communication analysis, stance detection, conversational thread modelling.
Twitter conversations around the Germanwings plane crash in the French Alps (March 2015), from the PHEME rumour dataset (Zubiaga, Liakata, Procter, Kochkina and colleagues; the complete release for rumour detection and veracity classification, figshare 6392078): 469 threads, each a source tweet and its replies, of which 238 were judged rumours by journalists and 231 not. Every rumour also carries its veracity as later established: 94 true, 111 false and 33 unverified. 4,489 tweets in all, with full tweet JSON. ECHO builds the reply network (4,020 reply links, each reply pointing to the tweet it answers) and labels each tweet with its thread's rumour status and, for source tweets, the veracity. Useful for rumour detection, rumour verification and modelling how conversations unfold. Annotations CC BY 4.0; Twitter retains the rights to tweet content. The archive PHEME_veracity.tar.bz2 is gzip-compressed despite its name (the name is the authors' own, kept so the checksum matches figshare): extract it with `tar xzf`.
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 1,412 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 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 1,200 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 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 1,050 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.
4chan
Twitter (X)