Secrets of More Likes: Understanding eWOM Popularity in Wine Tourism Reviews Through Text Complexity and Personal Disclosure

Jie Zheng, Xi Wang () and Yaning Mao
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Jie Zheng: College of Shanghai Lausanne Hospitality Management, Shanghai Business School, Shanghai 200233, China
Xi Wang: School of Culture and Creativity, Beijing Normal-Hong Kong Baptist University, Zhuhai 519087, China
Yaning Mao: Winterster School of Art, University of Southampton, Southampton SO17 1BJ, UK

Tourism and Hospitality, 2025, vol. 6, issue 3, 1-19

Abstract: Online reviews increasingly shape experiential travel decisions. This study investigates how structural and linguistic features of user-generated content influence peer endorsement in wine tourism. While prior research has explored review valence and credibility, limited attention has been paid to how micro-level textual and identity cues affect social approval metrics such as likes. Grounded in the Elaboration Likelihood Model, the analysis draws on 7942 TripAdvisor reviews using automated web scraping, readability metrics, and multivariate regression. Results indicate that location disclosure significantly increases likes, while higher textual complexity reduces endorsement. Title length and reviewer contributions function as peripheral cues, with an interaction between complexity and title length compounding cognitive effort. Findings refine dual-process persuasion theory and offer practical insights for content optimization in post-pandemic tourism engagement.

Keywords: online reviews; wine tourism; Elaboration Likelihood Model; user engagement; text readability; identity disclosure (search for similar items in EconPapers)
JEL-codes: Z3 Z30 Z31 Z32 Z33 Z38 (search for similar items in EconPapers)
Date: 2025
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