Urban functional regions using social media check-ins

Abstract

© 2018 IEEE Development of a city cultivates regions with different functions such as working areas and entertainment venues. People in a city usually travel among these regions in certain movement patterns. Identifying those regions will facilitate government management and promote further development of the city. In this paper, we proposed a framework to identify urban functional regions in Chengdu city based upon mobility pattern and point of interest (POIs) information extracted from mobile check-ins data. Firstly, unlike GPS trajectories, location check-ins were discontinuous. Thus, the typical mobility patterns of location check-ins was mined. Secondly, an arrival/departure matrix based on the typical mobility patterns was constructed to obtain the topics of regions by clustering POIs. Because we considered a region's function as our topics, we transferred the problem into a topic modeling problem, and applied an improved probabilistic topic model to infer functions of the regions. We evaluated our approach with 227,428 check-ins in Chengdu collected from Sina Weibo from April 12 2012 to February 16 2013. The results showed that our method outperformed baseline methods solely clustering POIs.