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

Mingming Cheng, Xin Jin, Ying Wang, Xiaowei Wang, Jinyan Chen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1237-1256
Number of pages20
JournalJournal of Travel Research
Volume62
Issue number6
DOIs
Publication statusPublished - Jul 2023

Keywords

  • gold coast
  • mega event
  • sequential pattern mining
  • tourist movement
  • Twitter

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Transportation
  • Tourism, Leisure and Hospitality Management

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