In e-commerce, researchers have found that consumer reviews with negative ratings are more likely to be perceived as helpful. While the negativity bias is well documented at the numerical rating level, there is less evidence on whether the existence of negative sentiments in textual review contents is perceived as being more helpful by consumers. To solve this problem, we introduce the prospect theory and cognitive dissonance theory. Utilizing a cross-sectional consumer review dataset collected from Amazon.com, we empirically demonstrate that the existence of negative sentiments can increase review helpfulness. Exploration of contingent factors suggests that the positive effect of the existence of negative sentiments is stronger for reviews with negative ratings and review with shorter length, and that easy-to-read reviews cast more salient positive influence. This paper combines the numerical rating and textual content of each review to explore confirmation bias. Our findings have important practical implications for review platforms.
Zhao, Cheng, "Are Negative Sentiments “Negative” for Review Helpfulness?" (2020). PACIS 2020 Proceedings. 22.
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