Generating vague neighbourhoods through data mining of passive web data
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 h...
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| Format: | Article |
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Taylor & Francis
2017
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| Online Access: | https://eprints.nottingham.ac.uk/47698/ |
| _version_ | 1848797607771504640 |
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| author | Brindley, Paul Goulding, James Wilson, Max L. |
| author_facet | Brindley, Paul Goulding, James Wilson, Max L. |
| author_sort | Brindley, Paul |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:06:34Z |
| format | Article |
| id | nottingham-47698 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:06:34Z |
| publishDate | 2017 |
| publisher | Taylor & Francis |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-476982020-05-04T19:17:41Z https://eprints.nottingham.ac.uk/47698/ Generating vague neighbourhoods through data mining of passive web data Brindley, Paul Goulding, James Wilson, Max L. 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. Taylor & Francis 2017-11-16 Article PeerReviewed Brindley, Paul, Goulding, James and Wilson, Max L. (2017) Generating vague neighbourhoods through data mining of passive web data. International Journal of Geographical Information Science, 32 (3). pp. 498-523. ISSN 1365-8824 Neighbourhoods Vague Geographies Geographic Information Retrieval Geocomputation http://www.tandfonline.com/doi/abs/10.1080/13658816.2017.1400549 doi:10.1080/13658816.2017.1400549 doi:10.1080/13658816.2017.1400549 |
| spellingShingle | Neighbourhoods Vague Geographies Geographic Information Retrieval Geocomputation Brindley, Paul Goulding, James Wilson, Max L. Generating vague neighbourhoods through data mining of passive web data |
| title | Generating vague neighbourhoods through data mining of passive web data |
| title_full | Generating vague neighbourhoods through data mining of passive web data |
| title_fullStr | Generating vague neighbourhoods through data mining of passive web data |
| title_full_unstemmed | Generating vague neighbourhoods through data mining of passive web data |
| title_short | Generating vague neighbourhoods through data mining of passive web data |
| title_sort | generating vague neighbourhoods through data mining of passive web data |
| topic | Neighbourhoods Vague Geographies Geographic Information Retrieval Geocomputation |
| url | https://eprints.nottingham.ac.uk/47698/ https://eprints.nottingham.ac.uk/47698/ https://eprints.nottingham.ac.uk/47698/ |