BILATTICE-BASED AGGREGATION OPERATORS FOR GRADUAL TRUST AND DISTRUST
Trust and distrust are two increasingly important metrics in social networks. Since many of these networks are very large, it is only natural that not all users know each other. To this aim, propagation and aggregation operators are often used to estimate (dis)trust relations for users that are not directly connected through the network. In this paper, we introduce bilattice-based aggregation approaches and show that they can be used to accurately predict trust and distrust predictions for the social networking site CouchSurfing.org.