Kota Tsubouchi

TL;DR: By April 15th (1 week into state of emergency), human mobility behavior decreased by around 50%, resulting in a 70% reduction of social contacts in Tokyo, showing the strong relationships with non-compulsory measures.

TL;DR: In this paper, the authors analyzed the temporal changes in human mobility behavior, social contact rates, and their correlations with the transmissibility of COVID-19, using mobility data collected from more than 200K anonymized mobile phone users in Tokyo.

TL;DR: The results show that in most cases delaying the notification delivery until an interruptible moment is detected is beneficial to users and results in significant reduction of user response time compared to delivering the notifications immediately.

TL;DR: Analysis of human mobility trajectories of over 1.9 million mobile phone users across three countries finds that, despite the diversity in socio-economic characteristics among the affected regions and the types of hazards, population recovery trends after significant displacement resemble similar patterns after all five disasters.

TL;DR: A low-rank bilinear Poisson regression model is proposed, for a novel and flexible representation of urban dynamics predictive analysis, and the following applications are introduced: regional event detection via irregularities, visualization ofurban dynamics corresponding to urban demographics, and extraction of urban demographics of unknown point of interests.