Looking into Socio-cognitive Relations between Urban Areas based on Crowd Movements Monitoring with Twitter

Abstract

Due to the proliferation of location-based information services, there is abundant urban information which makes us difficult to catch up with the characteristics and dynamics of our living space. However, nowadays, crowd lifelogs shared over social network sites are attracting a great deal of attention as a novel source to search for local information from the massive voices and lifelogs of crowds. In this regard, we can further look into urban images representing how we recognize a city in mind through the direct massive crowd experiences. In this work, we explore crowd-experienced local information over location-based social network sites to derive much better understandable and useful urban images. In detail, we propose a method to generate a socio-cognitive map where characteristic urban clusters are projected based on cognitive distance between urban areas. Specifically, in order to measure cognitive distances between urban clusters and examine their influential strengths, we observe crowd s movements over Twitter. Finally, we show an experimental result of generating a socio-cognitive map illustrating crowd-sourced cognitive relations between urban clusters in Kinki area, Japan.