Mapping destination images and behavioral patterns from user-generated photos: a computer vision approach

Zhang, Kun; Chen, Ye; Lin, Zhibin

doi:10.1080/10941665.2020.1838586

Mapping destination images and behavioral patterns from user-generated photos: a computer vision approach

Zhang, Kun; Chen, Ye; Lin, Zhibin

Authors

Kun Zhang

Ye Chen

Professor Zhibin Lin zhibin.lin@durham.ac.uk
Professor

Abstract

Destination image studies were traditionally based on questionnaire surveys, but the recent rise of user-generated content and social media big data analytics provide new opportunities for advancing tourism research. This study adopts one of the latest artificial intelligence computer vision technologies to identify the differences in the perceived destination image and behavioral patterns between residents and tourists from user-generated photos. Data were mined from Flickr, which yields 58,392 relevant geotagged photos taken in Hong Kong. The findings reveal that the perceptual differences between the two groups lay on seven types of perceptions. The differences in spatial distribution and behavioral trajectory were visualized through a series of maps. This study provides new insights into the destination image which has implications for the tourism promotion and spatial development of the destination.

Citation

Zhang, K., Chen, Y., & Lin, Z. (2020). Mapping destination images and behavioral patterns from user-generated photos: a computer vision approach. Asia Pacific Journal of Tourism Research, 25(11), 1199-1214. https://doi.org/10.1080/10941665.2020.1838586

Journal Article Type	Article
Acceptance Date	Oct 11, 2020
Online Publication Date	Nov 4, 2020
Publication Date	2020
Deposit Date	Nov 6, 2020
Publicly Available Date	May 4, 2022
Journal	Asia Pacific Journal of Tourism Research
Print ISSN	1094-1665
Electronic ISSN	1741-6507
Publisher	Taylor and Francis Group
Peer Reviewed	Peer Reviewed
Volume	25
Issue	11
Pages	1199-1214
DOI	https://doi.org/10.1080/10941665.2020.1838586
Public URL	https://durham-repository.worktribe.com/output/1257579

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Copyright Statement
This is an Accepted Manuscript of an article published by Taylor & Francis in the Asia Pacific Journal of Tourism Research on 4 November 2020, available online: http://www.tandfonline.com/10.1080/10941665.2020.1838586