Content dissimilarity and online review helpfulness: Contextual insights

Shan Wang, Shubhashis Karmakar, Fang Wang and Yanli Pei

Journal of Business Research, 2025, vol. 187, issue C

Abstract: As consumers navigate through online product reviews, they read and assess individual reviews within a broader context of product information, including product descriptions and preceding reviews. This research incorporates this information context to better understand online review helpfulness. Specifically, it studies the influence of content dissimilarity in online reviews, including topic and lexical dissimilarities compared to product descriptions and preceding reviews, respectively, on their perceived helpfulness to potential customers. An empirical analysis of approximately 1.6 million Amazon reviews reveals that readers prefer online product reviews that align with topics but differ in lexicon from product descriptions and preceding reviews. Moreover, the topic and lexical dissimilarities interact in affecting review helpfulness, and the impact of content dissimilarity varies across reviews for products of differing price levels. This research underscores the significance of assessing information utility within its contextual framework and highlights the importance of evaluating content at both the topical and lexical levels. It offers fresh insights for both scholars and practitioners in understanding and curating beneficial online information.

Keywords: Online customer reviews; Content dissimilarity; Contextual information; Online review helpfulness; Text analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbrese:v:187:y:2025:i:c:s0148296324005721

DOI: 10.1016/j.jbusres.2024.115068

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