Review Manipulation and Filtering on Digital Platforms
研究苹果应用商店数据发现，被平台过滤的正面和负面操纵评论都会提升应用排名，负面操纵评论更易被消费者识别，评论数量比评分方向更能影响消费者行为，对免费、游戏及大开发商应用影响更大。
Manipulated consumer reviews are a growing concern for digital platforms, undermining trust and distorting market outcomes. This study analyzes data from the Apple App Store to assess how both positive and negative manipulated reviews—later filtered by the platform—affect app sales rankings. Surprisingly, both one-star and five-star manipulated reviews initially boost app rankings, even when one-star reviews are intended to harm competitors. These effects can persist for weeks and take up to six months to reverse through platform filtering. Using text analysis, we find that negative manipulated reviews are linguistically more distinguishable from organic ones than are positive manipulated reviews, making them easier for consumers to spot. Our results show that review volume often outweighs valence in influencing consumer behavior, and that manipulated reviews have stronger effects on free apps, gaming apps, and apps from large developers. These findings underscore the urgency for platform managers to invest in faster, more accurate filtering systems, and highlight the need for policymakers to strengthen governance mechanisms to protect marketplace integrity and consumer trust.