A Hotel Ranking Method Through Online Reviews Considering the Cultural Background of Reviewers

Online reviews are an important influencing factor in consumer purchasing decisions, and consumers' diverse cultural backgrounds affect the expression of online reviews as well as decision-making process. This study proposes an integrated ranking method through online reviews. Specifically, the study constructs a fraudulent review detection model to detect fraudulent reviews. Then introduces the Hofstede's national cultural framework and cultural distance theory to propose a method for calculating the weighted sentiment values of reviews, and interval-valued Pythagorean fuzzy sets are used for representation. Finally, the ranking function is improved by introducing a weight factor to aggregate the ratings and reviews, and obtain the hotel ranking. To validate the proposed method, a case study is conducted using real hotel reviews. The results show that this method provides a suitable and differentiated ranking of alternatives for consumers in specific countries. This paper also offers insights for online review websites and hotel managers.

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Publication Details

Journal
International Journal of Fuzzy System Applications
Published
2025-03-22
DOI
https://doi.org/10.4018/ijfsa.371752
Primary Topic
Digital Marketing and Social Media
Type
article
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article

A Hotel Ranking Method Through Online Reviews Considering the Cultural Background of Reviewers

Yujia Liu, Jian Wu, Xiaoyi Du, Jing Shi
International Journal of Fuzzy System Applications
Digital Marketing and Social Media
article

A Hotel Ranking Method Through Online Reviews Considering the Cultural Background of Reviewers

Yujia Liu, Jian Wu, Xiaoyi Du, Jing Shi
article en

Abstract

Online reviews are an important influencing factor in consumer purchasing decisions, and consumers' diverse cultural backgrounds affect the expression of online reviews as well as decision-making process. This study proposes an integrated ranking method through online reviews. Specifically, the study constructs a fraudulent review detection model to detect fraudulent reviews. Then introduces the Hofstede's national cultural framework and cultural distance theory to propose a method for calculating the weighted sentiment values of reviews, and interval-valued Pythagorean fuzzy sets are used for representation. Finally, the ranking function is improved by introducing a weight factor to aggregate the ratings and reviews, and obtain the hotel ranking. To validate the proposed method, a case study is conducted using real hotel reviews. The results show that this method provides a suitable and differentiated ranking of alternatives for consumers in specific countries. This paper also offers insights for online review websites and hotel managers.

International Journal of Fuzzy System ApplicationsVol. 14(1)
Shanghai Maritime University (CN)
Openalex Percentile: Top 93%
Digital Marketing and Social Media
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A Hotel Ranking Method Through Online Reviews Considering the Cultural Background of Reviewers — Yujia Liu, Jian Wu, et al. · International Journal of Fuzzy System Applications (2025) | TGRS Research Map | TGRS