Impact of Anonymity on Consumers' Online Reviews

Abstract

Extant literature has studied the relationship between identity disclosure and online consumer reviews, yet no research has investigated the effects of the introduction of an “anonymous review” option on consumers' online reviews. With a unique restaurant review data set from a most popular online review platform in China, we exploit a natural experiment setup in which the platform launched a new function of “anonymous review” that allows reviewers' choosing not to disclose their own information while posting reviews. We ground in the theories of deindividuation and social presence, and the notion of negativity bias to investigate the effects of anonymity on consumers' online review provision in terms of their rating behavior and emotional expressions in review texts. The results show that the anonymity function implementation induces a decrease in overall ratings and a decrease (increase) in positive (negative) emotions on average. Furthermore, using the reviews after the policy change, we find that, compared to non‐anonymous reviews, anonymous ones are usually with lower ratings and more (less) negative (positive) emotions, which can further induce subsequent reviewers' negative reviews. Our findings underscore the doubled‐sides of an “anonymous review” function the public policy makers, platform and restaurant managers need to balance in practice.

Noisy Signals: Do Ratings’ Volatility Depend on the Length of the Consumption Span?

“…A potential explanation for this is that, as explained in Section 4, ratings are derived from the average of six items that capture hotel quality as a whole rather than the specific attributes of individual rooms. In line with identity disclosure and deindividualization theories (Deng et al, 2021), we find that anonymous guests tend to provide lower ratings. More precisely, other things being equal, review anonymity is associated with a 0.198-point drop in scores.…”

Affordances advancing user-created communication (UCC) in service: interactivity, visibility and anonymity

“…High anonymity may enable unintended and negative outcomes, such as cyberbullying, fake reviews and misinformation. Restaurant reviewers who can post anonymous online reviews are likelier to provide lower ratings and express more negative emotions, which may lead to negativity bias: the more a user is exposed to negative anonymous communication, the more likely they are to also leave negative anonymous communication (Deng et al, 2021). Perceived anonymity combined with frequent social media use can also lead to cyberbullying (Lowry et al, 2016).…”

Influence of travel distance and travel experience on travelers' online reviews: price as a moderator

“…(1) Quantitative attribute Review rating is a quantitative attribute of reviews reflecting consumers' satisfaction, which is used to scale review characteristics in most existing studies (Deng et al, 2021;Gao et al, 2018;Ho et al, 2017;Li, 2016;Zhang et al, 2016). It is an integer and usually ranges from 1 to 5 with one star representing the worst evaluation and five stars the best.…”

“…Review rating is a quantitative attribute of reviews reflecting consumers' satisfaction, which is used to scale review characteristics in most existing studies (Deng et al. , 2021; Gao et al.…”