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Social Interactions and Bias in the Evaluation of Online Reviews

Social Science Research Network(2020)

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摘要
User-generated content, online reviews in particular, has been increasingly integrated into the management of customer responses and therefore into the core operations of platforms. Despite the extensive studies on the generation of online reviews and their potential impacts, research is scant regarding the factors that might affect the evaluation of online reviews by peer groups. In this study, we focus on the bias in review evaluations and argue that social interactions in various forms on online review platforms contribute to the bias. Using a unique dataset from a major review platform, we find that, ceteris paribus, reviews posted by more socially engaged users receive more helpfulness votes than those by less socially engaged users. Similarly, users tend to vote for reviews written by their mutual followers than for those written by non-followers. In addition, we find that less socially engaged users review a broader range of products (or services) but are less likely to stay on the platform, which may further contribute to the bias in review evaluations. Our findings, therefore, underscore an important factor—social factors—contributing to the bias in review evaluations and have implications for the management of customer response, content quality, and operational performance of platforms.
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