Grasp of Disaster Situation and Support Need Inside Affected Area  with Social Sensing – An Analysis of Twitter Data Before and After the 2011 Great East Japan Earthquake Disaster Occurring –

Shosuke Sato; Kazumasa Hanaoka; Makoto Okumura; Shunichi Koshimura

doi:10.20965/jdr.2016.p0198

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JDR Vol.11 No.2 pp. 198-206

(2016)

doi: 10.20965/jdr.2016.p0198

Paper:

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Grasp of Disaster Situation and Support Need Inside Affected Area with Social Sensing – An Analysis of Twitter Data Before and After the 2011 Great East Japan Earthquake Disaster Occurring –

Shosuke Sato, Kazumasa Hanaoka, Makoto Okumura, and Shunichi Koshimura

International Research Institute of Disaster Science (IRIDeS), Tohoku University
Aoba 468-1, Aramaki, Aoba, Sendai 980-0845, Japan

Received:

October 1, 2015

Accepted:

January 21, 2016

Online released:

March 18, 2016

Published:

March 1, 2016

Keywords:

social media, Twitter, Common Operational Picture (COP), disaster information system, geo-information, disaster situation

Abstract

There are increasing expectations that social sensing, especially the analysis of social media text as a source of information for COP (Common Operational Picture), is useful for decision-making about responses to disasters. This paper reports on a geo-information and content analysis of three million Twitter texts sampled from Japanese Twitter accounts for one month before and after the 2011 Great East Japan Earthquake disaster. The results are as follows. 1) The number of Twitter texts that include geotag (latitude and longitude information) is too small for reliable analysis. However, a method of detecting the tweet’s location from the tweet’s text using GeoNLP (an automatic technology to tag geo-information from natural language text) is able to identify geo-information, and we have confirmed that many tweets were sent from stricken areas. 2) A comparison of Twitter data distribution before and after the disaster occurred does not identify clearly which areas were significantly affected by the disaster. 3) There were very few Twitter texts that included information about the damage in affected areas and their support needs.

Cite this article as:

S. Sato, K. Hanaoka, M. Okumura, and S. Koshimura, “Grasp of Disaster Situation and Support Need Inside Affected Area with Social Sensing – An Analysis of Twitter Data Before and After the 2011 Great East Japan Earthquake Disaster Occurring –,” J. Disaster Res., Vol.11 No.2, pp. 198-206, 2016.

Data files:

References

[1] National Institute of Information and Communications Technology, “DISAANA,” 2014, http://www.nict.go.jp/press/2014/11/05-1.html [accessed October 1, 2015]
[2] T. Rokuse, S. Nagashima, O. Uchida, and F. Toriumi, “A Proposal on Information Service System at the Time of Large-Scale Disaster Using Twitter,” Forum on Information Technology, Vol.4, No.12, pp. 651-652, August, 2013.
[3] T. Ishikara, A. Kawasaki, and K. Meguro, “Investigation of information sharing by Twitter users during the 2011 heavy snow disaster in San-in region of western Japan,” Journal of Social Safety Science, No.17, pp. 135-143, 2012.
[4] T. Sakaki, J. Marui, F. Toriumi, K. Shinoda, K. Kazama, S. Kurihara, and I. Noda, “Changes in social media use in large-scale disasters,” The Association for Natural Language Processing, No.18, pp. 1228-1231, 2012.
[5] T. Sakaki, M. Okazaki, and Y. Matsuo, “Earthquake shakes Twitter users: real-time event detection by social sensors,” Proceedings of the 19^th international conference on World wide web, pp. 851-860, 2010.
[6] National Institute of Informatics, GeoNLP, https://geonlp.ex.nii. ac.jp/ [accessed October 1, 2015]
[7] Ministry of Land, Infrastructure, Transport and Tourism: Tsunami inundation area data in the 2011 Great East Japan Earthquake disaster, http://fukkou.csis.u-tokyo.ac.jp/ [accessed October 1, 2015]
[8] O. Uchida, M. Kosugi, G. Endo, T. Funayama, K. Utsu, S. Tajima, M. Tomita, Y. Kajita, and Y. Yamamoto, “A Disaster Related Information Sharing System Based on the Utilization of Twitter,” Proceedings of the IEICE Engineering Sciences Society/NOLTA Society Conference, 2015.

This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.

[1] [1] National Institute of Information and Communications Technology, “DISAANA,” 2014, http://www.nict.go.jp/press/2014/11/05-1.html [accessed October 1, 2015]

[2] [2] T. Rokuse, S. Nagashima, O. Uchida, and F. Toriumi, “A Proposal on Information Service System at the Time of Large-Scale Disaster Using Twitter,” Forum on Information Technology, Vol.4, No.12, pp. 651-652, August, 2013.

[3] [3] T. Ishikara, A. Kawasaki, and K. Meguro, “Investigation of information sharing by Twitter users during the 2011 heavy snow disaster in San-in region of western Japan,” Journal of Social Safety Science, No.17, pp. 135-143, 2012.

[4] [4] T. Sakaki, J. Marui, F. Toriumi, K. Shinoda, K. Kazama, S. Kurihara, and I. Noda, “Changes in social media use in large-scale disasters,” The Association for Natural Language Processing, No.18, pp. 1228-1231, 2012.

[5] [5] T. Sakaki, M. Okazaki, and Y. Matsuo, “Earthquake shakes Twitter users: real-time event detection by social sensors,” Proceedings of the 19^th international conference on World wide web, pp. 851-860, 2010.

[6] [6] National Institute of Informatics, GeoNLP, https://geonlp.ex.nii. ac.jp/ [accessed October 1, 2015]

[7] [7] Ministry of Land, Infrastructure, Transport and Tourism: Tsunami inundation area data in the 2011 Great East Japan Earthquake disaster, http://fukkou.csis.u-tokyo.ac.jp/ [accessed October 1, 2015]

[8] [8] O. Uchida, M. Kosugi, G. Endo, T. Funayama, K. Utsu, S. Tajima, M. Tomita, Y. Kajita, and Y. Yamamoto, “A Disaster Related Information Sharing System Based on the Utilization of Twitter,” Proceedings of the IEICE Engineering Sciences Society/NOLTA Society Conference, 2015.