This paper proposes a new methodological framework to identify economic clusters over space and time. We employ a unique open source dataset of geolocated and archived business webpages and interrogate them using Natural Language Processing to build bottom-up classifications of economic activities. We validate our method on an iconic UK tech cluster - Shoreditch, East London. We benchmark our results against existing case studies and administrative data, replicating the main features of the cluster and providing fresh insights. As well as overcoming limitations in conventional industrial classification, our method addresses some of the spatial and temporal limitations of the clustering literature.

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17 June 2022

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Environment and Planning B: Urban Analytics and City Science 50(1) , pp.244-267, 2022

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DOI: 10.1177/23998083221108185

https://journals.sagepub.com/doi/full/10.1177/23998083221108185

This Journal article is published under the centre's Urban programme.