During the past few years, sellers have increasingly offered discounted or free products to selected reviewers of ecommerce platforms in exchange for their reviews. Such incentivized (and often very positive) reviews can improve the rating of a product which in turn sways other users’ opinions about the product.
Here, we examine the problem of detecting and characterizing incentivized reviews in two primary categories of Amazon products. We show that the key features of EIRs and normal reviews exhibit different characteristics.
Furthermore, we illustrate how the prevalence of EIRs has evolved and been affected by Amazon’s ban.
Our examination of the temporal pattern of submitted reviews for sample products reveals promotional campaigns by the corresponding sellers and their effectiveness in attracting other users.
Finally, we demonstrate that a classifier that is trained by EIRs (without explicit keywords) and normal reviews can accurately detect other EIRs as well as implicitly incentivized reviews. Overall, this analysis sheds an insightful light on the impact of EIRs on Amazon products and users.