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In this paper, consideration is given to the use of new forms of social network data as a means to enrich our understanding of complex structures and activity patterns in urban areas. Specifically, a sample of Twitter messages (‘tweets’) in the city of Leeds is assembled from publicly available sources, and spatial and temporal patterns in these data are demonstrated, with special reference to the geodemographic profiles of service users. It is argued that classical space-time models of individual behaviour provide one possible framework for the interpretation of patterns, and the process of attempting to classify activities is begun with reference to the geographical distribution, timing and, importantly, the content of messages. Some initial analysis is undertaken to examine emerging networks of interconnection between users and individual users’ spatio-temporal behaviour. In the discussion, it is suggested that the integration of this form of social data analysis with existing microscale representations and multi-agent models of city structure and dynamics will provide fertile ground for future research.
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Stored only when both papers are in the corpus — 4 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.