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Multilingual analysis of Twitter news in support of mass emergency events

: Zielinski, Andrea; Bügel, Ulrich

Fulltext urn:nbn:de:0011-n-2257197 (326 KByte PDF)
MD5 Fingerprint: 831f2a01409ddc4b1c37197065520801
Created on: 30.1.2013

Rothkrantz, L. ; Environmental Systems Research Institute -ESRI-:
ISCRAM 2012, 9th International Conference on Information Systems for Crisis Response and Management. Proceedings : Vancouver, Canada, April 2012
Vancouver: Simon Fraser University, 2012
ISBN: 978-0-86491-332-6
5 pp.
International Conference on Information Systems for Crisis Response and Management (ISCRAM) <9, 2012, Vancouver>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Social media are increasingly becoming a source for event-based early warning systems in the sense that they can help to detect natural disasters and support crisis management during or after disasters. In this work-in-progress paper we study the problems of analyzing multilingual twitter feeds for emergency events. The present work focuses on English as "lingua franca" and on under-resourced Mediterranean languages in endangered zones, particularly Turkey, Greece, and Romania Generally, as local civil protection authorities and the population are likely to respond in their native language. We investigated ten earthquake events and defined four language-specific classifiers that can be used to detect earthquakes by filtering out irrelevant messages that do not relate to the event. The final goal is to extend this work to more Mediterranean languages and to classify and extract relevant information from tweets, translating the main keywords into English. Preliminary results indicate that such a filter has the potential to confirm forecast parameters of tsunami affecting coastal areas where no tide gauges exist and could be integrated into seismographic sensor networks.