A data driven approach to mapping urban neighbourhoodsTools Brindley, Paul, Goulding, James and Wilson, Max L. (2014) A data driven approach to mapping urban neighbourhoods. In: 22nd ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 4-7 November 2014, Dallas, Texas, USA. Full text not available from this repository.
Official URL: http://doi.acm.org/10.1145/2666310.2666473
AbstractNeighbourhoods have been described by the UK Secretary of State for Communities and Local Government as the “building blocks of public service society”. Despite this, difficulties in data collection combined with the concept’s subjective nature have left most countries lacking official neighbourhood definitions. This issue has implications not only for policy, but for the field of computational social science as a whole (with many studies being forced to use administrative units as proxies despite the fact that these bear little connection to resident perceptions of social boundaries). In this paper we illustrate that the mass linguistic datasets now available on the internet need only be combined with relatively simple linguistic computational models to produce definitions that are not only probabilistic and dynamic, but do not require a priori knowledge of neighbourhood names.
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