Assessing the Credibility of Nodes on Multiple-Relational Social Networks

With the development of the Internet, social network is changing people’s daily lives. In many social networks, the relationships between nodes can be measured. It is an important application to predict trust link, find the most reliable node and rank nodes. In order to implement those applications, it is crucial to assess the credibility of a node. The credibility of a node is denoted as the expected value, which can be evaluated by similarities between the node and its neighbors. That means the credibility of a node is high while its behaviors are reasonable. When multiple-relational networks are becoming prevalent, we observe that it is possible to apply more relations to improve the performance of assessing the credibility of nodes. We found that trust values among one type of nodes and similarity scores among different types of nodes reinforce each other towards better and more meaningful results. In this paper, we introduce a framework that computes the credibility of nodes on a multiple-relational network. The experiment result on real data shows that our framework is effective.