Silva, TH;
Vaz de Melo, POS;
Almeida, JM;
Musolesi, M;
Loureiro, AAF;
(2017)
A large-scale study of cultural differences using urban data about eating and drinking preferences.
Information Systems
, 72
pp. 95-116.
10.1016/j.is.2017.10.002.
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Abstract
Traditional ways to study urban social behavior, e.g. surveys, are costly and do not scale. Recently, some studies have been showing new ways of obtaining data through location-based social networks (LBSNs), such as Foursquare, which could revolutionize the study of urban social behavior. We use Foursquare check-ins to represent user preferences regarding eating and drinking habits. Considering datasets differing in terms of volume of data and observation window size, our results indicate that spatio-temporal eating and drinking habits of users voluntarily expressed in LBSNs has the potential to explain cultural habits of the users. From this, we propose a methodology to identify cultural boundaries and similarities across populations at different scales, e.g., countries, cities, or neighborhoods. This methodology is extensively evaluated in several aspects. For instance, by proposing some variations of it disregarding some of the considered dimensions, as well as analyzing the results using datasets from different periods and window of observation. The results indicate that our proposed methodology is a promising approach for automatic cultural habits separation, which could enable new urban services.
| Type: | Article |
|---|---|
| Title: | A large-scale study of cultural differences using urban data about eating and drinking preferences |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.is.2017.10.002 |
| Publisher version: | https://doi.org/10.1016/j.is.2017.10.002 |
| 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: | Science & Technology, Technology, Computer Science, Information Systems, Computer Science, Location-based social network, Large scale assessment, Urban data mining, Cross-cultural study, Foursquare, SOCIAL-NETWORKS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices 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 Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10051295 |
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