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 geo-tag data and verbal explanatory factors using tweet data. The non-verbal explanatory factors include distance between home and office, time taken in travelling by walking or public transport, etc. On the other hand, the verbal explanatory factors include external and psychological factors. 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.
