Shen, Y; Karimi, K; Law, S; (2017) Encounter and its configurational logic: Understanding spatiotemporal co-presence with road network and social media check-in data. In: Proceedings of the 11th Space Syntax Symposium. (pp. 111.1-111.22). Instituto Superior Técnico, Portugal: Lisbon, Portugal.

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Abstract

Public space facilitates the social interaction between people. It is widely accepted that the connection between spaces creates the possibility of the mutual visibility between people. The relationship between spatial configuration and the spatiotemporal encounters, however, has rarely been investigated explicitly in empirical cases. The focus of this study is two folded: firstly, it examines the way to measure spatiotemporal encounters between different groups of people based on their mobility records; secondly, it investigates how the design of the built environment contributes to physical co-presence on spatial and temporal dimensions. Using ubiquitous individual social media check-in data in Central Shanghai, China, this study proposes a framework for quantifying physical face-to-face co-presence patterns between the defined local random walkers and the remote visitors across time in every street. In the introduced People-Space-Time (PST) model, social capital is conceptualised as an integration among social difference, spatial distance (metric and geometrical distance) and time distance. The reliability of the applied data and the effectiveness of the introduced methods are validated by the investigations of the scaling nature of the extracted mobility patterns and the correlation between the outputs and surveyed data. The produced spatiotemporal patterns of face-toface co-presence reveal that city centres and the large-scale urban complexes (e.g., transport hubs, shopping malls, stadiums, etc.) are ideal places for people to encounter. The results of the regression analyses demonstrate that spatial and functional centrality measures are significant variables for predicting spatiotemporal co-presence in streets, but in which the functional centrality structures maintain a higher standard of explanatory power than the spatial network. The temporal complexity of the co-presence is revealed by the temporally shifting performance of the integrated regression models across time. The findings in this study yield that it is the spatio-functional interaction influencing spatiotemporal variation of the physical encounter between people, and reclaim the necessity of adding fine-scale land-use patterns in the traditional configurational analysis for deeply understanding the social processes with urban big data in the contemporary digitalised cities.

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