Electronic Healthcare. 4th International Conference, eHealth 2011, Málaga, Spain, November 21-23, 2011, Revised Selected Papers

Research Article

An Analysis of Twitter Messages in the 2011 Tohoku Earthquake

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  • @INPROCEEDINGS{10.1007/978-3-642-29262-0_8,
        author={Son Doan and Bao-Khanh Vo and Nigel Collier},
        title={An Analysis of Twitter Messages in the 2011 Tohoku Earthquake},
        proceedings={Electronic Healthcare. 4th International Conference, eHealth 2011, M\^{a}laga, Spain, November 21-23, 2011, Revised Selected Papers},
        proceedings_a={E-HEALTH},
        year={2012},
        month={5},
        keywords={Twitter social media earthquake surveillance natural language processing},
        doi={10.1007/978-3-642-29262-0_8}
    }
    
  • Son Doan
    Bao-Khanh Vo
    Nigel Collier
    Year: 2012
    An Analysis of Twitter Messages in the 2011 Tohoku Earthquake
    E-HEALTH
    Springer
    DOI: 10.1007/978-3-642-29262-0_8
Son Doan1,*, Bao-Khanh Vo1,*, Nigel Collier1,*
  • 1: National Institute of Informatics
*Contact email: doan@nii.ac.jp, khanhvo@nii.ac.jp, collier@nii.ac.jp

Abstract

Social media such as Facebook and Twitter have proven to be a useful resource to understand public opinion towards real world events. In this paper, we investigate over 1.5 million Twitter messages () for the period 9 March 2011 to 31 May 2011 in order to track awareness and anxiety levels in the Tokyo metropolitan district to the 2011 Tohoku Earthquake and subsequent tsunami and nuclear emergencies. These three events were tracked using both English and Japanese tweets. Preliminary results indicated: 1) close correspondence between Twitter data and earthquake events, 2) strong correlation between English and Japanese tweets on the same events, 3) tweets in the native language play an important roles in early warning, 4) tweets showed how quickly Japanese people’s anxiety returned to normal levels after the earthquake event. Several distinctions between English and Japanese tweets on earthquake events are also discussed. The results suggest that Twitter data can be used as a useful resource for tracking the public mood of populations affected by natural disasters as well as an early warning system.