A concept-level approach to the analysis of online review helpfulness. (May 2016)

• Record Type: Journal Article
• Authors: Qazi, Aika; Shah Syed, Karim Bux; Raj, Ram Gopal; Cambria, Erik; Tahir, Muhammad; Alghazzawi, Daniyal
• Is Part Of: Computers in human behavior. Volume 58(2016)
• Page Start: 75
• Page End: 81
• Publication Date: 2016-05
• Subjects: Online reviews -- Review helpfulness -- Electronic commerce -- Suggestive reviews; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2015.12.028
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: Helpfulness of online reviews serves multiple needs of different Web users. Several types of factors can drive reviews' helpfulness. This study focuses on uninvestigated factors by looking at not just the quantitative factors (such as the number of concepts), but also qualitative aspects of reviewers (including review types such as the regular, comparative and suggestive reviews and reviewer helpfulness) and builds a conceptual model for helpfulness prediction. The set of 1500 reviews were randomly collected from TripAdvisor.com across multiple hotels for analysis. A set of four hypotheses were used to test the proposed model. Our results suggest that the number of concepts contained in a review, the average number of concepts per sentence, and the review type contribute to the perceived helpfulness of online reviews. The regular reviews were not statistically significant predictors of helpfulness. As a result, review types and concepts have a varying degree of impact on review helpfulness. The findings of this study can provide new insights to e-commerce retailers in understanding the importance of helpfulness of reviews. Highlights: We have examined the factors that participate in online reviews helpfulness. The regular, comparative and suggestive are included as qualitative aspect. The numbers of concepts in opinion types are examined as quantitative factors. Further challenges are discussed for coming researchers.