Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/98457
PIRA download icon_1.1View/Download Full Text
Title: Harnessing social media to understand tourist travel patterns in muti-destinations
Authors: Chen, J 
Becken, S
Stantic, B
Issue Date: Nov-2022
Source: Annals of tourism research empirical insights, Nov. 2022, v. 3, no. 2, 100079
Abstract: Understanding travel patterns is helpful for decision-makers to draw insights from consumers' perspectives. This work took advantage of social media and analysed tourists' travel patterns from the length of itineraries and duration of stay. Using Chinese tourists in Australia as a case study, results showed that most visitors prefer to stay in two core destinations, with an average duration of 8.5 days, while adding one destination increases the stay by around 2.5 days and caps at approximately 14 days. The travel patterns were further analysed by social network analysis and explained the network structure using core-periphery theory. The results were compared with official national survey data and demonstrated encouraging accuracy, which provides practical implications for destination planning and management.
Keywords: Travel patterns
Social network analysis
Social media
Core-periphery theory
Centrality
Publisher: Elsevier Ltd
Journal: Annals of tourism research empirical insights 
EISSN: 2666-9579
DOI: 10.1016/j.annale.2022.100079
Rights: © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Chen, J., Becken, S., & Stantic, B. (2022). Harnessing social media to understand tourist travel patterns in muti-destinations. Annals of Tourism Research Empirical Insights, 3(2), 100079 is available at https://doi.org/10.1016/j.annale.2022.100079.
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
1-s2.0-S2666957922000477-main.pdf1.66 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

72
Citations as of Apr 14, 2025

Downloads

52
Citations as of Apr 14, 2025

SCOPUSTM   
Citations

4
Citations as of Jun 21, 2024

WEB OF SCIENCETM
Citations

4
Citations as of Nov 14, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.