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Generating vague neighbourhoods through data mining of passive web data

Brindley, Paul; Goulding, James; Wilson, Max L.

Authors

Paul Brindley



Abstract

Neighbourhoods have been described as \the building blocks of public services society". Their subjective nature, however, and the resulting difficulties in collecting data, means that in many countries there are no officially defined neighbourhoods either in terms of names or boundaries. This has implications not only for policy but also business and social decisions as a whole. With the absence of neighbourhood boundaries many studies resort to using standard administrative units as proxies. Such administrative geographies, however, often have a poor fit with those perceived by residents. Our approach detects these important social boundaries by automatically mining the Web en masse for passively declared neighbourhood data within postal addresses. Focusing on the United Kingdom (UK), this research demonstrates the feasibility of automated extraction of urban neighbourhood names and their subsequent mapping as vague entities. Importantly, and unlike previous work, our process does not require any neighbourhood names to be established a priori.

Citation

Brindley, P., Goulding, J., & Wilson, M. L. (in press). Generating vague neighbourhoods through data mining of passive web data. International Journal of Geographical Information Science, 32(3), https://doi.org/10.1080/13658816.2017.1400549

Journal Article Type Article
Acceptance Date Oct 31, 2017
Online Publication Date Nov 16, 2017
Deposit Date Oct 31, 2017
Publicly Available Date Nov 17, 2018
Journal International Journal of Geographical Information Science
Print ISSN 1365-8816
Electronic ISSN 1365-8824
Publisher Taylor & Francis Open
Peer Reviewed Peer Reviewed
Volume 32
Issue 3
DOI https://doi.org/10.1080/13658816.2017.1400549
Keywords Neighbourhoods, Vague Geographies, Geographic Information Retrieval, Geocomputation
Public URL http://eprints.nottingham.ac.uk/id/eprint/47698
Publisher URL http://www.tandfonline.com/doi/abs/10.1080/13658816.2017.1400549
Copyright Statement Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf
Additional Information This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Geographical Information Science on 16 Nov 2017 available online: http://www.tandfonline.com/10.1080/13658816.2017.1400549

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Copyright Statement
Copyright information regarding this work can be found at the following address: http://eprints.nottingham.ac.uk/end_user_agreement.pdf





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