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Using Digital Trace Data to Identify Regions and Cities...

by Christina M Brelsford, Gautam Thakur, Rudy Arthur, Hywel Williams
Publication Type
Conference Paper
Journal Name
Book Title
Proceedings of the 2nd International Workshop on Advances in Resilient and Intelligent Cities (ARIC 2019)
Publication Date
Page Numbers
1 to 4
Conference Name
27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Conference Location
Chicago, Illinois, United States of America
Conference Sponsor
Conference Date

A greater understanding of human dynamics as they play out in both physical space and through inter-personal communication is vital for the design and development of intelligent and resilient cities. Physical context provides insight in to the space-time distribution of population and their activity patterns, while inter-personal communication can, for the first time, be measured at scale through virtual interactions. The confluence of these two enables spatial social network analysis in the built environment for edge computing, knowledge discovery, and artificial intelligence activities. In this work, we propose a novel method to discover such dynamics. We use a dataset of 72 million tweets to develop a spatially embedded network of communication, and then use community detection algorithms to explore regional and urban delineation in the United States. We find that the broad spatial delineation of communities and community sub-structure is consistent with major United States socio-cultural regions, states, and major metropolitan areas. We describe how these methods could be extended to generate a measure of socially cohesive regions that can be consistently applied anywhere there is a sufficiently rich data source. We hope the proposed methods will generate new perspectives on smart and resilient cities.