Lai, J;
Lansley, G;
Haworth, J;
Cheng, T;
(2020)
A name‐led approach to profile urban places based on geotagged Twitter data.
Transactions in GIS
, 24
(4)
pp. 858-879.
10.1111/tgis.12599.
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Abstract
Place is a concept that is fundamental to how we orientate and communicate space in our everyday lives. Crowdsourced social media data present a valuable opportunity to develop bottom‐up inferences of places that are integral to social activities and settings. Conventional location‐led approaches use a predefined spatial unit to associate data and space with places, which cannot capture the richness of urban places (i.e., spatial extents and their dynamic functions). This article develops a name‐led framework to overcome these limitations in using social media data to study urban places. The framework first derives place names from georeferenced Twitter data combining text mining and spatial point pattern analysis, then estimates the spatial extents by spatial clustering, and further extracts their dynamic functions with time, which makes up a complete place profile. The framework is tested on a case study in Camden Borough, London and the results are evaluated through comparisons to the Foursquare point of interest data. This name‐led approach enables the shift from space‐based analysis to place‐based analysis of urban space.
Type: | Article |
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Title: | A name‐led approach to profile urban places based on geotagged Twitter data |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1111/tgis.12599 |
Publisher version: | http://dx.doi.org/10.1111/tgis.12599 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Social Sciences, Geography, SPACE-TIME, CITIES |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10091855 |




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