The Illusion of Authenticity in Online Reviews: Truth Bias and the Role of Valence
Authors: Yin, Dezhi; Bond, Samuel D.; Zhang, Han
Journal: Information Systems Research (2026)
<jats:p>As consumer awareness of fake online reviews grows, platforms face increasing challenges in maintaining trust. Although skepticism toward reviews is rising, our research finds that consumers still exhibit a “truth bias,” meaning that they tend to accept individual reviews as genuine—even when fake review detection rates are low. This highlights the need for platforms to proactively identify and address fraudulent content rather than relying on user reporting of suspected fakes, which is largely ineffective. Platforms might also consider labeling suspected fake reviews with warning badges or fact-check indicators. Additionally, we find that truth bias is stronger for negative reviews, making fake negative reviews particularly impactful and damaging. Consequently, platforms should prioritize detecting and mitigating fake negative reviews over fake positive ones. Our findings also suggest that structuring reviews into separate positive and negative sections or allowing (or defaulting to) valence-based review sorting might reduce consumer likelihood of being fooled by fake negative reviews. These insights inform platform policy by emphasizing the importance of proactive fraud…