REVIEW MODERATION TRANSPARENCY AND ONLINE REVIEWS: EVIDENCE FROM A NATURAL EXPERIMENT

• 成果类型: Review
• 署名作者: Jiang, Lianlian (Dorothy); Ravichandran, T.; Kuruzovich, Jason
• 署名单位: University of Houston System; University of Houston; Rensselaer Polytechnic Institute
• 刊物名称: MIS QUARTERLY
• ISSN/ISSBN: 0276-7783
• DOI: 10.25300/MISQ/2023/16216
• 发表日期: 2023
• 页码: 1693-1708
• 关键词: User-Generated Content; Word-of-mouth; NEGATIVITY BIAS; INFORMATION; IMPACT

摘要

This paper empirically investigates how review moderation transparency affects the volume, length, and negativity of reviews. A change to the Yelp platform in 2010, introducing review moderation and displaying filtered reviews, created a natural experiment. We used a panel dataset of online reviews from the same set of restaurants on both the Yelp and TripAdvisor platforms in a difference-in-differences (DID) model to test how review moderation transparency affected our outcome variables. We found that increasing review moderation transparency negatively affects review volume but positively affects review negativity. The results also indicate that providing review moderation transparency reduces review length, especially for reviews with positive sentiment. Our findings suggest that providing review moderation transparency induces users to invest less effort in review contributions, especially when they are submitting positive reviews. We discuss the theoretical and practical implications of these results as they relate to the design and use of online review platforms.