Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99672
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Title: A sequential pattern mining approach to tourist movement : the case of a mega event
Authors: Cheng, M
Jin, X
Wang, Y 
Wang, X
Chen, J 
Issue Date: Jul-2023
Source: Journal of travel research, July 2023, v. 62, no. 6, p. 1237-1256
Abstract: The movement of tourists has important economic and social implications for destination management. However, tracking and analyzing such movement can be a challenge both conceptually and methodologically. Using four different sequential pattern mining algorithms, this study investigates the movement of international visitors during the Gold Coast Commonwealth Games (GC2018) at the level of a specific destination through Twitter data. Results indicate that sequential pattern mining is a powerful technique to reveal complex travel patterns and provides insights into the potential associated destinations of visitors beyond the current point-to-point analysis. This approach can assist destination management and event organizers in identifying the event’s contribution to tourists’ local visitation.
Keywords: Gold coast
Mega event
Sequential pattern mining
Tourist movement
Twitter
Publisher: SAGE Publications
Journal: Journal of travel research 
ISSN: 0047-2875
EISSN: 1552-6763
DOI: 10.1177/00472875221126433
Rights: This is the accepted version of the publication "Cheng, M., Jin, X., Wang, Y., Wang, X., & Chen, J., A Sequential Pattern Mining Approach to Tourist Movement: The Case of a Mega Event, Journal of Travel Research (62(6)) pp. 1237–1256. Copyright © 2022 (The Author(s)). DOI: 10.1177/00472875221126433".
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