Detection and extracting of emergency knowledge from twitter streams

Authors:
Bernhard Klein;Xabier Laiseca;Diego Casado-Mansilla;Diego López-de-Ipiña;Alejandro Prada Nespral
Affiliations:
Deusto Institute of Technology, DeustoTech, University of Deusto, Bilbao, Spain;Deusto Institute of Technology, DeustoTech, University of Deusto, Bilbao, Spain;Deusto Institute of Technology, DeustoTech, University of Deusto, Bilbao, Spain;Deusto Institute of Technology, DeustoTech, University of Deusto, Bilbao, Spain;Treelogic, Llanera, Asturias, Spain
Venue:
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
Year:
2012

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Abstract

Increasingly, more important information is being shared through Twitter. New opportunities arise to use this tool to detect emergencies and extract crucial information about the scope and nature of that event. A major challenge for the extraction of emergency event information from Twitter is represented by the unstructured and noisy nature of tweets. Within the SABESS project we propose a combined structural and content based analysis approach. We use social network analysis to identify reliable tweets and content analysis techniques to summarize key emergency facts.