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 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 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 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 1,563 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 1,237 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.