Lai, J;
Cheng, T;
Lansley, G;
(2017)
Improved targeted outdoor advertising based on geotagged social media data.
Annals of GIS
, 23
(4)
pp. 237-250.
10.1080/19475683.2017.1382571.
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Abstract
With as many as 4 million passenger journeys within the London Underground system every weekday, the advertisement spaces across the stations hold considerable potential. However, the planning of specific advertisements across time and space is difficult to optimize as little is known about passers-by. Therefore, in order to generate detailed and quantifiable spatio-temporal information which is particular to each station area, we have explored local social media data. This research demonstrates how local interests can be mined from geotagged Tweets by using Latent Dirichlet Allocation, an unsupervised topic modelling method. The relative popularity of each of the key topics is then explored spatially and temporally between the station areas. Overall, this research demonstrates the value of using Geographical Information System and text-mining techniques to generate valuable spatio-temporal information on popular interests from Twitter data.
| Type: | Article |
|---|---|
| Title: | Improved targeted outdoor advertising based on geotagged social media data |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/19475683.2017.1382571 |
| Publisher version: | http://dx.doi.org/10.1080/19475683.2017.1382571 |
| Language: | English |
| Additional information: | © 2017 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Targeted advertisement, geotagged social media data, LDA, topic modelling, spatio-temporal analysis |
| 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 UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10026080 |
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