Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/326331 
Year of Publication: 
2024
Citation: 
[Journal:] Cogent Business & Management [ISSN:] 2331-1975 [Volume:] 11 [Issue:] 1 [Article No.:] 2364837 [Year:] 2024 [Pages:] 1-24
Publisher: 
Taylor & Francis, Abingdon
Abstract: 
The burgeoning panda tourism market in China is attracting an increasing number of domestic and international tourists. This study focuses on the Chengdu Research Base of Giant Panda Breeding as a case study and utilizes Latent Dirichlet Allocation (LDA) modeling and topic-based sentiment analysis to conduct text mining on online travel reviews in both English and Chinese languages. LDA modeling was employed to identify topics within online reviews, with a subsequent evaluation of the importance of each topic. Furthermore, topic-based sentiment analysis was conducted to assess the performance of different topics. Through importance-performance analysis, this study interprets the destination image disparities between English and Chinese reviews from a cross-cultural perspective. The research findings validate the effectiveness of destination image analysis methods, providing valuable insights for tailoring distinct destination marketing strategies that target tourists from diverse linguistic backgrounds.
Subjects: 
Destination image
marketing strategy
cross-cultural
LDA model
sentiment analysis
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article

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