Title: Discovering Latent Patterns of Urban Cultural Interactions in WeChat for Modern City Planning,
Abstract: Cultural activity is an inherent aspect of urban life and the success of a
modern city is largely determined by its capacity to offer generous cultural
entertainment to its citizens. To this end, the optimal allocation of cultural
establishments and related resources across urban regions becomes of vital
importance, as it can reduce financial costs in terms of planning and improve
quality of life in the city, more generally. In this paper, we make use of a
large longitudinal dataset of user location check-ins from the online social
network WeChat to develop a data-driven framework for cultural planning in the
city of Beijing. We exploit rich spatio-temporal representations on user
activity at cultural venues and use a novel extended version of the traditional
latent Dirichlet allocation model that incorporates temporal information to
identify latent patterns of urban cultural interactions. Using the
characteristic typologies of mobile user cultural activities emitted by the
model, we determine the levels of demand for different types of cultural
resources across urban areas. We then compare those with the corresponding
levels of supply as driven by the presence and spatial reach of cultural venues
in local areas to obtain high resolution maps that indicate urban regions with
lack of cultural resources, and thus give suggestions for further urban
cultural planning and investment optimisation.