Modeling clusters from the ground up: A web data approach

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.

Automated summary

This paper proposes a new methodological framework for identifying economic clusters using Natural Language Processing and spatial analysis of geolocated business webpages. Validating the method on a UK tech cluster, the study replicates the main features of the cluster and provides fresh insights. The proposed method overcomes limitations of conventional industrial classification and addresses spatial and temporal limitations in clustering research.