We propose an embedding-based clustering approach and a method for the automated labelling of clusters. While information disseminated in social media can lead to valuable insights, emergency services and researchers face the challenge of information overload as data quickly exceeds the manageable amount. Past studies in the domains of information systems have analysed the potentials and barriers of social media in emergencies. Markus Bayer, Marc-André Kaufhold, Christian Reuter (2021) Information Overload in Crisis Management: Bilingual Evaluation of Embedding Models for Clustering Social Media Posts in EmergenciesProceedings of the European Conference on Information Systems (ECIS).
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