International Journal on Semantic Web and Information Systems · 2007 · 171 citations · 0 references
Social SciencesSocial PsychologyPublic OpinionSocial InfluenceSocial PerceptionReputationReputation ManagementSocial JudgmentComplex SocietiesPerceived TrustworthinessReputation ModelingReputation SystemsTrust PredictionTrust Score ComputationTrustworthinessUser Trust Evaluation
Trust metrics are used to answer questions like “Should I trust this person?” but most research assumes a single, universally agreed global quality score for each user, which is unrealistic in today’s connected world where interactions with unknown people are common. The study argues that because controversial users exist, local trust metrics that predict a user's trustworthiness personalized to each judge are needed. The authors use computational experiments to develop local trust metrics that predict a user's trustworthiness based on the individual judge's perspective. Data from Epinions.com shows that many users are controversial, lacking a global trust score, and that using local versus global trust metrics can lead to cultural extremes such as tyranny of the majority or echo chambers.
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.