Trustcircle: A Novel Trust Framework for creating a Personalised Recommender System that helps Evaluate Trustworthiness in Sharing Economy Services

Evaluating trustworthiness of peers prior to engaging in any collaborative or transactional activity is crucial in sharing economy platforms. Current systems are heuristic in nature, limited in their approach to model trust. They provide non-personalized, unstructured data leading to increased time and effort while assessing trustworthiness of available options. These systems also fail to adapt to user’s changing trust profile for different contexts and situations. In this paper, we propose a trust framework that helps structure factors essential in evaluating trustworthiness of peers and services they offer or seek. We apply this framework to build a recommender system that learns user-specific dynamic trust profile and provide personalized trustworthy recommendations. We implement this system in context of peer-to-peer ride-sharing where the system uses features from the framework, user feedback and platform usage data to learn a personalized dynamic trust profile for recommending the most trustworthy rides.