28 datasets credited to Ofli, Ferda.
28 datasets.
A Twitter dataset of 7,376 tweets from california_wildfires_2018, collected by Alam et al. for california_wildfires_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the california_wildfires_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 2,242 tweets from canada_wildfires_2016, collected by Alam et al. for canada_wildfires_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the canada_wildfires_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 76,484 tweets across 19 events, 10 humanitarian categories, collected by Alam et al. for 19 natural disaster events (2016-2019). Each record contains tweet text, humanitarian category label, event name, train/dev/test split. Largest publicly available human-annotated crisis dataset with 76,484 tweets across 19 events. Suitable for crisis informatics, humanitarian response, text classification, social media analysis.
A Twitter dataset of 3,933 tweets from cyclone_idai_2019, collected by Alam et al. for cyclone_idai_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the cyclone_idai_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,563 tweets from ecuador_earthquake_2016, collected by Alam et al. for ecuador_earthquake_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the ecuador_earthquake_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,515 tweets from greece_wildfires_2018, collected by Alam et al. for greece_wildfires_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the greece_wildfires_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,613 tweets from hurricane_dorian_2019, collected by Alam et al. for hurricane_dorian_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_dorian_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 6,264 tweets from hurricane_florence_2018, collected by Alam et al. for hurricane_florence_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_florence_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 9,112 tweets from hurricane_harvey_2017, collected by Alam et al. for hurricane_harvey_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_harvey_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 9,399 tweets from hurricane_irma_2017, collected by Alam et al. for hurricane_irma_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_irma_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,278 tweets from hurricane_maria_2017, collected by Alam et al. for hurricane_maria_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_maria_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,654 tweets from hurricane_matthew_2016, collected by Alam et al. for hurricane_matthew_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the hurricane_matthew_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
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 2,195 tweets from kaikoura_earthquake_2016, collected by Alam et al. for kaikoura_earthquake_2016 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the kaikoura_earthquake_2016 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 7,984 tweets from kerala_floods_2018, collected by Alam et al. for kerala_floods_2018 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the kerala_floods_2018 event. Suitable for crisis informatics, humanitarian response, text classification.
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 Twitter dataset of 1,880 tweets from midwestern_us_floods_2019, collected by Alam et al. for midwestern_us_floods_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the midwestern_us_floods_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 1,958 tweets from pakistan_earthquake_2019, collected by Alam et al. for pakistan_earthquake_2019 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the pakistan_earthquake_2019 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 2,015 tweets from puebla_mexico_earthquake_2017, collected by Alam et al. for puebla_mexico_earthquake_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the puebla_mexico_earthquake_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
A Twitter dataset of 560 tweets from srilanka_floods_2017, collected by Alam et al. for srilanka_floods_2017 crisis. Each record contains tweet text, humanitarian category label, train/dev/test split. Human-annotated crisis tweets from the srilanka_floods_2017 event. Suitable for crisis informatics, humanitarian response, text classification.
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).
Twitter (X)