What makes a helpful online review? Empirical evidence on the effects of review and reviewer characteristics

Purpose: The reviews submitted by users are the foundation of user-generated content (UGC) platforms. However, the rapid growth of users brings the problems of information overload and spotty content, which makes it necessary for UGC platforms to screen out reviews that are really helpful to users. The authors put forward in this paper the factors influencing review helpfulness voting from the perspective of review characteristics and reviewer characteristics. Design/methodology/approach: This study uses 8,953 reviews from 20 movies listed on Douban.com with variables focusing on review characteristics and reviewer characteristics that affect review helpfulness. To verify the six hypotheses proposed in the study, Stata 14 was used to perform tobit regression. Findings: Findings show that review helpfulness is significantly influenced by the length, valence, timeliness and deviation rating of the reviews. The results also underlie that a review submitted by a reviewer who has more followers and experience is more affected by review characteristics. Originality/value: Previous literature has discussed the factors that affect the helpfulness of reviews; however, the authors have established a new model that explores more comprehensive review characteristics and the moderating effect reviewer characteristics have on helpfulness. In this empirical research, the authors selected a UGC community in China as the research object. The UGC community may encourage users to write more helpful reviews by highlighting the characteristics of users. Users in return can use this to establish his/her image in the community. Future research can explore more variables related to users. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2020-0186.