A Cross-cultural Study on the Influence of Textual Topics on Review Helpfulness of Cultural Products

Abstract

Abstract: Based on theories in cross-cultural psychology, this study employs a data-driven topic model to compare how different content topics in online review texts of books affect the evaluation of review helpfulness by Chinese and American consumers. Using the Latent Dirichlet Allocation (LDA) topic model, we extract eight general topics about books from 50,270 reviews posted on the websites of Amazon China and Amazon USA. By comparing the impact of various topics on review helpfulness between Chinese and American reviews, we find that review content related to Reading Experience/Purchasing Advice and bilateral or neutral Attribute Evaluation is more useful to Chinese consumers than to U.S. consumers. By contrast, Chinese and American consumers do not differ in their assessment of the helpfulness of review content related to informational topics. These findings enrich the literature on cross-cultural comparisons of online reviews and factors influencing review usefulness. They could also help cross-border e-commerce retailers optimize the design of their online review systems by providing more targeted product reviews for consumers of different cultural background.

Key words: online reviews, cross-cultural differences, review helpfulness, text mining, topic modelling

Xiao Xian, Qiu Lingyun, Pang Jun. A Cross-cultural Study on the Influence of Textual Topics on Review Helpfulness of Cultural Products[J]. Management Review, 2025, 37(2): 163-174.

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