Exploration and Analysis on Spatial Disparity of Urban Residents' Activities Based on Check-in Data in Sina Weibo

Abstract

Based on the concept of ‘Everyone is a sensor’, the spatial and located information derived from mobile devices can objectively reflect the population spatial activity characteristics, which could represent the geographic distribution of population activity space. Based on more than 860,000 samples collected from Sina Weibo, by implementing kernel density analysis and local spatial autocorrelation Getis-OrdGi statistical index, we explore the resident activity space distribution. The result shows that resident activity conducts a significant difference of space distribution among three districts in Wuhan. For the purpose of investigating the cause of these huge differences, we divided the POI into eight categories, and analyze the space aggregation of density of check-in information of each categories, we found out that: resident activity distribution is independent of the POI quantity, but conversely highly related to the POI spatial distribution and regional economic development. Hence, in order to further investigate the correlation between them, we draw the scatter plot of the 2014 GDP data and Weibo check-in data from the three districts, which consequently, prove that they are positive relative and validated through Pearson coefficients. Our research indicated that Weibo check-in data can ultimately reflect the resident activity distribution; furthermore, this kind of distribution is positively related to regional economic development level.