Bootstrapping Referral Systems With Social Network Information

Abstract

This thesis addresses the challenge of facilitating human interactions in solving problems. To this end, it assigns an agent to each user, and models a social network as a multiagent system. A user's agent helps them by sending out and responding to queries on their behalf. Each agent makes its decisions based on its models of the expertise and trustworthiness of other agents. However, such models are not trivial to construct and maintain. This thesis develops an approach wherein the models are seeded based upon information extracted from the user's emails and from existing social networking sites. The main contribution of this thesis is in the specification of heuristics by which expertise and trustworthiness can be computed. It also provides a general schema and methodology by which additional sources of social information can be incorporated.