Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces

Ren, Y, Tomko, M, Salim, F, Chan, J and Sanderson, M 2018, 'Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces', EPJ Data Science, vol. 7, no. 1, pp. 1-21.


Document type: Journal Article
Collection: Journal Articles

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Title Understanding the predictability of user demographics from cyber-physical-social behaviours in indoor retail spaces
Author(s) Ren, Y
Tomko, M
Salim, F
Chan, J
Sanderson, M
Year 2018
Journal name EPJ Data Science
Volume number 7
Issue number 1
Start page 1
End page 21
Total pages 21
Publisher Springer Open
Abstract Understanding the association between customer demographics and behaviour is critical for operators of indoor retail spaces. This study explores such an association based on a combined understanding of customer Cyber (online), Physical, and (some aspects of) Social (CPS) behaviour, at the conjunction of corresponding CPS spaces. We combine the results of a traditional questionnaire with large-scale WiFi access logs, which capture customer cyber and physical behaviour. We investigate the predictability of user demographics based on CPS behaviors captured from both sources. We find (1) strong correlations between users' demographics and their CPS behaviors; (2) log-recorded cyber-physical behavior reflects well data captured in the corresponding questionnaire; (3) different CPS behaviors contribute differently to the predictability of demographic attributes; and (4) the predictability of user demographics from logs is comparable to questionnaire-based data. As such, our study provides strong support for demographic studies based on large-scale logs data capture.
Subject Information Retrieval and Web Search
Keyword(s) logs
questionnaire
predictability of user demographics
DOI - identifier 10.1140/epjds/s13688-017-0128-2
Copyright notice © The Authors 2018. Creative Commons Attribution 4.0 International License.
ISSN 2193-1127
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