A Probabilistic Matrix Factorization Method for Link Sign Prediction in Social Networks

Abstract

In this paper, we consider the link sign prediction in social networks with friend and foe relationships. We view the sign prediction as a user-to-user recommendation problem with trust or distrust information. Not only do we take the topological relationships such as the social structural balance and status theories into consideration, but also the social factors that whether a user is trustworthy and whether the user easily trust others are involved. We propose a probabilistic matrix factorization method with social trust and distrust ensembles and the structural theories from social psychology in order to predict link signs in social networks. The experimental results show that our proposed method outperforms those of the previous studies on this problem.