Abstract
The 2011 Great East Japan Earthquake and 2016 Kumamoto earthquakes had a great impact on numerous people all over the world. In this paper, we focus on social media and the mental health of 2016 Kumamoto earthquake survivors. We first focus on the users who had experienced an earthquake and track their sentiments before and after the disaster using Twitter as a sensor. Consequently, we found that their emotional polarities switch from nervous during earthquakes and return to normal after huge earthquakes. However, we also found that some people did not go back to normal even after huge earthquakes subside. Against this background, we attempted to identify survivors who are suffering from serious mental distress concerning earthquakes. Our experimental results suggest that, besides the frequency of words related to earthquakes, the deviation in sentiment and lexical factors during the earthquake represent the mental conditions of Twitter users. We believe that the findings of this study will contribute to early mental health care for people suffering the aftereffects of a huge disaster.
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- 1.
IBM®Watson Explorer Advanced Edition Analytical Components V11.0 is a trademark in the United States and/or other countries of International Business Machines Corporation.
- 2.
We extracted expressions which occur with high frequency and correlation by using WEX and defined them as earthquake-related words:
(earthquake), 
(aftershock), 
(immediate report), 
(shelter), 
(shaking) and 
(goods). - 3.
The actual annotation was a three class label: a user who does not care about the disaster, a user who is slightly concerned with the disaster, and user who is severely affected by the disaster. This annotation was conducted by two human annotators, and Cohen’s kappa for that is 0.75. By merging the first two classes into one class, we created an experimental dataset with two classes.
- 4.
(earthquake), 
(aftershock), 
(immediate report), 
(shelter), 
(shaking) and 
(goods).References
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Acknowledgements
We are grateful to Koichi Kamijoh, Hiroshi Kanayama, Masayasu Muraoka, and the members of the IBM Research - Tokyo text mining team for their helpful discussions.
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Aoki, T., Yoshikawa, K., Nasukawa, T., Takamura, H., Okumura, M. (2018). Detecting Earthquake Survivors with Serious Mental Affliction. In: Hasida, K., Pa, W. (eds) Computational Linguistics. PACLING 2017. Communications in Computer and Information Science, vol 781. Springer, Singapore. https://doi.org/10.1007/978-981-10-8438-6_1
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