Status Downgrade : The Impact of Losing Status on a User-generated Content Platform

Platform recognition in the form of non-financial incentives such as badges, status, and ranks are commonly employed to incentivize user contributions. We study one such incentive, "status", in the context of a user-generated content platform, specifically a third-party online restaurant-review platform. While previous literature has extensively focused on the impact of non-financial incentives on subsequent contributions from rewarded users, we focus on the temporal impact on user contribution when such incentives are withdrawn. Particularly, we explore whether, after a contributor loses status, the intrinsic quality and perceived quality of contents generated by the contributor are affected differently. We utilize natural language processing (NLP) techniques to extract these quality metrics from the textual content of online reviews in our dataset. Using a unique empirical strategy, we show that the intrinsic quality of reviews significantly decreases after a reviewer is demoted by a platform. However, these reviews, despite their lower intrinsic quality, continue to be perceived highly useful by platform users. We also find that characteristics related to temporal association with the platform or with the elevated status, do not moderate the effect of status loss on intrinsic or perceived quality of reviews written post-demotion. These results have significant implications for platform managers who design systems related to status and how such status should be shown to platform users