A Sequential Pattern Mining Approach to Tourist Movement: The Case of a Mega Event

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Author(s)
Cheng, Mingming
Jin, Xin
Wang, Ying
Wang, Xiaowei
Chen, Jinyan
Griffith University Author(s)
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2023
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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.

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Journal of Travel Research

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62

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6

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This work is covered by copyright. You must assume that re-use is limited to personal use and that permission from the copyright owner must be obtained for all other uses. If the document is available under a specified licence, refer to the licence for details of permitted re-use. If you believe that this work infringes copyright please make a copyright takedown request using the form at https://www.griffith.edu.au/copyright-matters.

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Subject

Tourism

Urban and regional planning

Social Sciences

Hospitality, Leisure, Sport & Tourism

Social Sciences - Other Topics

gold coast

sequential pattern mining

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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, 2023

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