“Popularity Effect” in User-Generated Content: Evidence from Online Product Reviews

TLDR

Online product reviews heavily influence consumer decisions, yet the processes that generate them—especially the role of user interactions such as subscriptions—remain poorly understood. The study investigates whether such subscription interactions promote review production and what characteristics of reviews they generate. Using data from a major product‑review platform that allows user subscriptions, the authors apply panel data and flexible matching techniques to analyze the effect. They find that more popular users write more and more objective reviews, but their numeric ratings become systematically more negative and variable, revealing a previously undocumented trade‑off.

Abstract

Online product reviews are increasingly important for consumer decisions, yet we still know little about how reviews are generated in the first place. In an effort to gather more reviews, many websites encourage user interactions such as allowing one user to subscribe to another. Do these interactions actually facilitate the generation of product reviews? More importantly, what kind of reviews do such interactions induce? We study these questions using data from one of the largest product review websites where users can subscribe to one another. By applying both panel data and a flexible matching method, we find that as users become more popular, they produce more reviews and more objective reviews; however, their numeric ratings also systematically change and become more negative and more varied. Such trade-off has not been previously documented and has important implications for both product review and other user-generated content websites.