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Author (up) Yuya Shibuya; Hideyuki Tanaka pdf  isbn
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  Title Detecting Disaster Recovery Activities via Social Media Communication Topics Type Conference Article
  Year 2019 Publication Proceedings of the 16th International Conference on Information Systems for Crisis Response And Management Abbreviated Journal Iscram 2019  
  Volume Issue Pages  
  Keywords Social Media, Topic modeling, Socio-economic recovery, Used-car demand, Housing demand.  
  Abstract Enhancing situational awareness by mining social media has been widely studied, but little work has been done

focusing on recovery phases. To provide evidence to support the possibility of harnessing social media as a sensor

of recovery activities, we examine the correlations between topic frequencies on Twitter and people’s socioeconomic

recovery activities as reflected in the excess demand for used cars and housing, after the Great East

Japan Earthquake and Tsunami of 2011. Our research suggests that people in the disaster-stricken area

communicated more about recovery and disaster damages when they needed to purchase used cars, while the nonlocal

population communicated more about going to and supporting the disaster-stricken area. On the other hand,

regarding the excess demand for housing, when the local population of the disaster-stricken area started to resettle,

they communicated their opinions more than in other periods about disaster-related situations.
 
  Address The University of Tokyo, Japan  
  Corporate Author Thesis  
  Publisher Iscram Place of Publication Valencia, Spain Editor Franco, Z.; González, J.J.; Canós, J.H.  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-84-09-10498-7 Medium  
  Track T8- Social Media in Crises and Conflicts Expedition Conference 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2019)  
  Notes Approved no  
  Call Number Serial 1889  
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