Description
In today’s connected world, it is possible and indeed quite common to interact with un-known people whose reliability is unknown. Trust metrics are a technique for answering questions such as “Should I trust this person?” However, most of the current research assumes that every user has a global quality score everyone agrees on and the goal of the technique is just to predict this correct value. We show on data from a real and large user community, Epinions.com, that such an assumption is not realistic because there is a significant portion of what we call controversial users, users who are trusted by many and distrusted by many: a global agreement about the trustworthiness value of these users does not exist. We argue, using computational experiments, that the existence of controversial users (a normal phenomenon in complex societies) demands local trust metrics, techniques able to predict the trustworthiness of a user in a personalized way, depending on the very personal views of the judging user as opposed to most commonly used global trust metrics, which assume a unique value of reputation for every single user. The implications of such an analysis deal with the very foundations of what we call society and culture and we conclude discussing this point by comparing the two extremes of culture that can be induced by the two different kinds of trust metrics: tyranny of the majority and echo chambers.