Trustable aggregation of online ratings

Abstract

The average of the customer ratings on a product, which we call reputation, is one of the key factors in online purchasing decision of a product. There is, however, no guarantee in the trustworthiness of the reputation since it can be manipulated rather easily. In this paper, we define false reputation as the problem of the reputation to be manipulated by unfair ratings, and design a general framework that provides trustable reputation. For this purpose, we propose TRUEREPUTATION, an algorithm that iteratively adjusts the reputation based on the confidence of customer ratings.