Extensive Experimental Validation of a Personalized Approach for Coping with Unfair Ratings in Reputation Systems

Abstract

The unfair rating problem exists when a buying agent models the trustworthiness of selling agents by also relying on ratings of the sellers from other buyers in electronic marketplaces, that is in a reputation system. In this article, we first analyze the capabilities of existing approaches for coping with unfair ratings in different challenging scenarios, including ones where the majority of buyers are dishonest, buyers lack personal experience with sellers, sellers may vary their behavior, and buyers may provide a large number of ratings. We then present a personalized modeling approach (PMA) that has all these capabilities. Our approach allows a buyer to model both the private reputation and public reputation of other buyers to determine whether these buyers' ratings are fair. More importantly, in this work, we focus on experimental comparison of our approach with two key models in a simulated dynamic e-marketplace environment. We specifically examine the above mentioned scenarios to confirm our analysis and to demonstrate the capabilities of our approach. Our study thus provides the extensive experimental support for the personalized approach that can be effectively employed by reputation systems to cope with unfair ratings.

Collectivism, face concern and Chinese-style lurking among university students: the moderating role of trait mindfulness

“…Online social anxiety can be viewed as an extension of offline social anxiety in the context of virtual interactions, characterized by an irrational fear of being scrutinized or evaluated by others in social situations (Morrison and Heimberg, 2013 ). The cognitive behavioral model of social anxiety (Lu et al, 2019 ) suggests that individuals who have strong desire to uphold their reputation (Zhang, 2011 ) tend to engage in active and responsible behaviors within their social circles to cultivate a favorable self-image. However, when confronted with situations that could lead to face loss, such as receiving aggressive or hostile responses or observing mistreatment from other group members, worrying about information being disregarded or damaging one's own and the collective reputation, individuals are prone to experiencing excessive fear of potential embarrassment or humiliation known as social anxiety (Liu and Cheng, 2023 ).…”

Robustness of Trust Models and Combinations for Handling Unfair Ratings

“…In the context of e-commerce, cheating behaviors or attack strategies can be categories as Seller Cheating Behaviors and Advisor Cheating Behaviors. Although the effectiveness of various attack strategies on trust models, including those suitable for e-commerce, has been studied in many other works (e.g., Hussain et al [2007], Zhang et al [2008], Hoffman et al [2009], Feng et al [2010] and Zhang [2011]), there is usually a lack of detailed experimental studies, especially the evaluation and comparison of a comprehensive set of unfair rating attack strategies on different trust models.…”