Abstract
This paper clarifies the occurrence factors of commuters unable to return home and the returning-home decision-making at the time of the Great East Japan Earthquake by using Twitter data. First, to extract the behavior data from the tweet data, we identify each user’s returning-home behavior using support vector machines. Second, we create non-verbal explanatory factors using geotag data and verbal explanatory factors using tweet data. Then, we model users’ returning-home decision-making by using a discrete choice model and clarify the factors quantitatively. Finally, by sensitivity analysis, we show the effects of the existence of emergency evacuation facilities and line of communication.
Cite
CITATION STYLE
Hara, Y. (2013). Returning-Home Analysis in Tokyo Metropolitan Area at the time of the Great East Japan Earthquake using Twitter Data. In 6th International Joint Conference on Natural Language Processing, IJCNLP 2013 - Proceedings of the Workshop on Language Processing and Crisis Information (pp. 44–50). Asian Federation of Natural Language Processing. https://doi.org/10.5715/jnlp.20.315
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