No abstract

Information overload is an increasing problem, and as information available continues to grow in volume, current filtering techniques are proving inefficient. Social network users, and people in general, tend to prioritize recommendations coming from people they are acquainted to, or trust. This research proposes a trust model that will estimate a trust value for content and content creators on an online rating system with social network capabilities.This research introduces the concept of social distance, which is drawn from clustering methods applied to the social network user base; and incorporates said distance in the estimation of trust, as well as user generated ratings. The trust value estimated will serve as a metric for filtering and sorting content of any kind based on the trustworthiness of the creator.