A prediction framework on the helpfulness of reviews for processing Chinese and English hotel reviews

Abstract

Purpose In the field of hospitality, most studies use English reviews and neglect non-English sources. The purpose of this paper is to exploit a predictive framework for review helpfulness that can process both Chinese and English textual comments. Design/methodology/approach This study develops some methods for feature extraction from Chinese online reviews, extracts more comprehensive predictors and proposes a novel prediction framework of classification before regression. Hofstede’s cultural theory is used to explain differences in the determinants of the helpfulness of reviews in Chinese and English. Findings The findings reveal that travelers from various countries do have discrepant perspectives on reviews helpfulness. Chinese tourists pay more attention to the reviewer profiles, whereas American tourists pay more attention to the review-related features. Practical implications This research offers hoteliers with actionable implications for meeting the needs of travelers from dissimilar cultural societies. The authors’ prediction framework can be used by website developers to create a review helpfulness rating system that allows visitors to acquire beneficial information. Originality/value On the one hand, the methods developed for extracting features of Chinese review, the hybrid set of features with several novel predictors and the prediction framework proposed in this study contribute to the methodology. On the other hand, this study is one of the few articles based on Hofstede’s cultural theory to guide a cross-cultural study on reviews helpfulness in hotel sector, which in turn contributes to the theory.