Exploring cross-cultural disparities in tourists' perceived images: a text mining and sentiment analysis study using LDA and BERT-BILSTM models
Abstract
Purpose
Tourists with different cultural backgrounds think and behave differently. Accurately capturing and correctly understanding cultural differences will help tourist destinations in product/service planning, marketing communication and attracting and retaining tourists. This research employs Hofstede's cultural dimensions theory to analyse the variations in destination image perceptions of Chinese-speaking and English-speaking tourists to Xiamen, a prominent tourist attraction in China.
Design/methodology/approach
The evaluation utilizes a two-stage approach, incorporating LDA and BERT-BILSTM models. By leveraging text mining, sentiment analysis and t-tests, this research investigates the variations in tourists' perceptions of Xiamen across different cultures.
Findings
The results reveal that cultural disparities significantly impact tourists' perceived image of Xiamen, particularly regarding their preferences for renowned tourist destinations and the factors influencing their travel experience.
Originality/value
This research pioneers applying natural language processing methods and machine learning techniques to affirm the substantial differences in the perceptions of tourist destinations among Chinese-speaking and English-speaking tourists based on Hofstede's cultural theory. The findings furnish theoretical insights for destination marketing organizations to target diverse cultural tourists through precise marketing strategies and illuminate the practical application of Hofstede's cultural theory in tourism and hospitality.
Keywords
Acknowledgements
Funding: This work was supported by Fujian Provincial Federation of Social Science, under Grant FJ2021B161; Joint Project Grant for Research on Science and Technology Innovation Strategy in Fujian Province (2022R0143).
Author contributions: Conceptualization, Q.C. and Q.J.; methodology, Q.C., R.L. and S.X.; software, R.L. and S.X.; validation, Q.C., S.X. and R.L.; formal analysis, Q.C.; investigation, S.X.; resources, R.L. and S. Y.; data curation, S.X. and R.L.; writing – original draft preparation, Q.C.; writing – review and editing, R.L.; visualization, S.X.; supervision, Q.J.; project administration, Q.C.; funding acquisition, Q.C. All authors have read and agreed to the published version of the manuscript.
Conflict of interest: The authors declare no conflicts of interest.
Data availability statement: The data supporting this study's findings are available from the corresponding author upon reasonable request.
Citation
Chen, Q., Liu, R., Jiang, Q. and Xu, S. (2024), "Exploring cross-cultural disparities in tourists' perceived images: a text mining and sentiment analysis study using LDA and BERT-BILSTM models", Data Technologies and Applications, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/DTA-10-2023-0645
Publisher
:Emerald Publishing Limited
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