Analysis of effectiveness of tsunami evacuation principles in the 2011 Great East Japan tsunami by using text mining

Nam Yi Yun, Seok Won Lee

    Research output: Contribution to journalArticle

    4 Citations (Scopus)

    Abstract

    Evacuation of the 2011 Great East Japan Earthquake and Tsunami was a large-scale evacuation of over thousands of people escaping from the earthquake-induced tsunami. The survivors’ evacuation experiences provided valuable insights into the factors that helped with survival and some very important practical issues regarding tsunami evacuation. Therefore, this article analyzes an effectiveness of tsunami evacuation principles from descriptive comments from the survivors and the non-survivors in the 2011 disaster using text mining method. As a result using the Naïve Bayesian classifier, it identifies some of the evacuation behaviors differences taken by the survivors or by the non-survivors under the disaster as an effectiveness of the evacuation principles, and attempts to understand how to provide more practical instructions. Therefore, these results give effective recommendations for evacuation preparation against catastrophic earthquake and tsunami disasters in the future.

    Original languageEnglish
    JournalMultimedia Tools and Applications
    DOIs
    Publication statusAccepted/In press - 2014 Nov 14

    Fingerprint

    Tsunamis
    Disasters
    Earthquakes
    Classifiers

    Keywords

    • Disaster mitigation
    • Evacuation principle
    • Human impact
    • Naïve Bayes classifier
    • Text Mining
    • The 2011 Great East Japan earthquake and tsunami

    ASJC Scopus subject areas

    • Media Technology
    • Hardware and Architecture
    • Computer Networks and Communications
    • Software

    Cite this

    Analysis of effectiveness of tsunami evacuation principles in the 2011 Great East Japan tsunami by using text mining. / Yun, Nam Yi; Lee, Seok Won.

    In: Multimedia Tools and Applications, 14.11.2014.

    Research output: Contribution to journalArticle

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