Finding the bias and prestige of nodes in networks based on trust scores

Many real-life graphs such as social networks and peer-topeer networks capture the relationships among the nodes by using trust scores to label the edges. Important usage of such networks includes trust prediction, finding the most reliable or trusted node in a local subgraph, etc. For many of these applications, it is crucial to assess the prestige and bias of a node. The bias of a node denotes its propensity to trust/mistrust its neighbours and is closely related to truthfulness. If a node trusts all its neighbours, its recommendation of another node as trustworthy is less reliable. It is based on the idea that the recommendation of a highly biased node should weigh less. In this paper, we propose an algorithm to compute the bias and prestige of nodes in networks where the edge weight denotes the trust score. Unlike most other graph-based algorithms, our method works even when the edge weights are not necessarily positive. The algorithm is iterative and runs in O(km) time where k i...

• Type: Journal
• Year: 2011
• Where: WWW
• Authors: Abhinav Mishra, Arnab Bhattacharya
• Keywords: Algorithms, Bias, Internet Technology, Node, WWW 2011