Urban area characterization based on crowd behavioral lifelogs over Twitter
Personal and Ubiquitous Computing
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Geo-social media represents geo-tagged crowd-sourced media emerged from the wide-spread dissemination of smartphones and the availability of social media during daily social activities. Nowadays, with such novel media as a fertile ground to observe a variety of social phenomena, we can explore geo-social knowledge with the unprecedented scale of crowd lifelogs. In this article, we will overview our pioneering work that has been conducted to explore and exploit geo-social knowledge utilizing geo-tagged twitter data. In our study, we established a model to look into crowd behavior and mental status that are observed from local twitter data. Based on our novel perspective to examine the macro-scale crowd lifestyle patterns, we attempted to explore and exploit three types of geo-social knowledge; local event detectio , urban area characterization, and crowd sense of distance in urban space. In the conclusion, we will summarize our contribution to take advantages of the explosively growing geo-social media and briefly describe our future direction.