Journal of Management Information Systems

Volume 39 Number 1 2022 pp. 218-246

Effects of Online Crowds on Self-Disclosure Behaviors in Online Reviews: A Multidimensional Examination

Choi, HanByeol Stella, Oh, Wonseok, Kwak, Chanhee, Lee, Junyeong, and Lee, Heeseok


In online environments (i.e., product review sites in our case), consumers are increasingly interacting and socializing with many “strangers” (i.e., online crowds) as well as sharing personal and product information. Drawing from social norms theory, we examine how the multiple aspects of online crowds affect their self-disclosure behaviors as they provide online reviews and investigate the extent to which prior experience moderates this relationship. Our analysis of data from a leading apparel rental site in the United States uncovers that individuals are inclined to conform to the self-disclosure behaviors of a crowd and divulge more personal information as self-disclosure variance within the group increases. Conversely, individuals are more likely to conceal personal information as a review page becomes crowded. The findings reveal that a reviewer’s prior experience of writing a review on the website weakens conformity behavior and reduces the effects of crowdedness. The prior experience also positively interacts with self-disclosure variance in a crowd. Based on these results, we present theoretical implications to literature on social norms and privacy, prior experience, and online reviews. This study also has managerial implications for firms interested in content generation by online reviewers and in review systems where user-generated content is essential.

Key words and phrases: Online crowds, social norms, online self-disclosure, online reviews, fixed-effect two-stage least squares models