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Author (up) Hristo Tanev; Vanni Zavarella; Josef Steinberger pdf 
  Title Monitoring disaster impact: detecting micro-events and eyewitness reports in mainstream and social media Type Conference Article
  Year 2017 Publication Proceedings of the 14th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal ISCRAM 2017  
  Volume Issue Pages 592-602  
  Keywords Natural language processing; machine learning; crisis computing; disaster effects; social media  
  Abstract This paper approaches the problem of monitoring the impact of the disasters by mining web sources for the events, caused by these disasters. We refer to these disaster effects as “micro-events”. Micro-events typically following a large disaster include casualties, damage on infrastructures, vehicles, services and resource supply, as well as relief operations. We present natural language grammar learning algorithms which form the basis for building micro-event detection systems from data, with no or minor human intervention, and we show how they can be applied to mainstream news and social media for monitoring disaster impact. We also experimented with applying statistical classifiers to distill, from social media situational updates on disasters, eyewitness reports from directly affected people. Finally, we describe a Twitter mining robot, which integrates some of these monitoring techniques and is intended to serve as a multilingual content hub for enhancing situational awareness.  
  Address European Commission Joint Research Centre; University of West Bohemia  
  Corporate Author Thesis  
  Publisher Place of Publication Albi, France Editor Tina Comes, Frédérick Bénaben, Chihab Hanachi, Matthieu Lauras, Aurélie Montarnal, eds  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN Medium  
  Track Social Media Studies Expedition Conference 14th International Conference on Information Systems for Crisis Response And Management  
  Notes Approved no  
  Call Number Serial 1493  
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