Lloyd, A;
Cheshire, J;
(2016)
Mining Consumer Insights from Geo-Located Social Media Datasets.
In:
(Proceedings) GISRUK 2016: 24th GIS Research UK Conference, 30 March-1 April 2016, London, UK.
GIS Research UK (GISRUK): London, UK.
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Abstract
Twitter's geo-referenced and opinion rich data offers the potential to determine when, where and what people Tweet about retail. However, the utility of Twitter to extract consumer insights specific to retail centres remains relatively under-investigated. Retail related Tweets were identified and their spatial attributes examined in relation to centre locations. An advanced form of kernel density estimation revealed that retail related Tweets might be a good indicator of areas of elevated retail activity within the UK. The work further highlights that to examine Twitter data, heuristics that account for the underlying geographic distribution of users are necessary. The approach demonstrates potential methodologies and applications for less conventional datasets, such as those derived from social media data, to previously under-researched areas.
Type: | Proceedings paper |
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Title: | Mining Consumer Insights from Geo-Located Social Media Datasets |
Event: | GISRUK 2016: 24th GIS Research UK Conference, 30 March-1 April 2016, London, UK |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | http://www.gre.ac.uk/ach/services/events/gisruk201... |
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 Media; Twitter; Geo-Reference; Retail; Consumer |
UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography |
URI: | https://discovery-pp.ucl.ac.uk/id/eprint/1545172 |
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