Review Manipulation and Filtering on Digital Platforms

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.