This resource consists of 19 humanitarian crises datasets. Each dataset contains crisis-related posts collected from Twitter, human-labeled tweets, dictionaries of out-of-vocabulary(OOV) words, word2vec embeddings, and other related tools. Please cite the following article, if you use any of these resources in your research.
Muhammad Imran, Prasenjit Mitra, and Carlos Castillo: Twitter as a Lifeline: Human-annotated Twitter Corpora for NLP of Crisis-related Messages.
In Proceedings of the 10th Language Resources and Evaluation Conference (LREC), pp. 1638-1643. May 2016, Portorož, Slovenia. [Bibtex
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