The Polarity of Online Reviews: Prevalence, Drivers and Implications

Abstract

In this research, the authors investigate the prevalence, robustness, and possible reasons underlying the polarity of online review distributions, with the majority of the reviews at the positive end of the rating scale, a few reviews in the midrange, and some reviews at the negative end of the scale. Compiling a large data set of online reviews—over 280 million reviews from 25 major online platforms—the authors find that most reviews on most platforms exhibit a high degree of polarity, but the platforms vary in the degree of polarity on the basis of how selective customers are in reviewing products on the platform. Using cross-platform and multimethod analyses, including secondary data, experiments, and survey data, the authors empirically confirm polarity self-selection, described as the higher tendency of consumers with extreme evaluations to provide a review as an important driver of the polarity of review distributions. In addition, they describe and demonstrate that polarity self-selection and the polarity of the review distribution reduce the informativeness of online reviews.