From Credit and Risk to Trust: Towards a Credit Flow Based Trust Model for Social Networks
Association for Computing Machinery
Trust management is a paramount issue in social networks. Existing models based on global reputation are simplistic as they do not support personalised measures for individual users. Models based on local trust propagation tend to be too subjective to be reliable as they do not consider a social network in its entirety. More importantly, neither model has taken the risk factor into the consideration of trust management. In this paper, we contribute a novel trust model that allows personalised measures to be naturally established on objective grounds through tracing credit flows within a social network, where the trust between a pair of users can be derived from the credit flowing from one into the other and the relative risk disparity between them. This model uses power flows in an electrical grid as a metaphor for the credit flows in a social network and is based on the hypothesis that the credit flows in a social network are similar in nature to the power flows in an electrical grid. Experiments with a real-world dataset have proved the hypothesis and the results have shown that the credit flow based trust model can derive not only personalised but also more accurate trust measures than existing models do.