Advanced SIM Capabilities Supporting Trust-Based Applications
NordSec '09 Proceedings of the 14th Nordic Conference on Secure IT Systems: Identity and Privacy in the Internet Age
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
Social Network Analysis and Mining for Business Applications
ACM Transactions on Intelligent Systems and Technology (TIST)
FlowTrust: trust inference with network flows
Frontiers of Computer Science in China
Subject classification of research papers based on interrelationships analysis
Proceedings of the 2011 workshop on Knowledge discovery, modeling and simulation
FloodTrust for Improved Trust Transitivity
WI-IAT '11 Proceedings of the 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Volume 02
Mitigating the malicious trust expansion in social network service
ISPEC'10 Proceedings of the 6th international conference on Information Security Practice and Experience
A group trust metric for identifying people of trust in online social networks
Expert Systems with Applications: An International Journal
Meme ranking to maximize posts virality in microblogging platforms
Journal of Intelligent Information Systems
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By the immense growth of the Web-Based Social Networks (WBSNs), the role of trust in connecting people together through WBSNs is getting more important than ever. In other words, since the probability of malicious behavior in WBSNs is increasing, it is necessary to evaluate the reliability of a person before trying to communicate with. Hence, it is desirable to find out how much a person should trust another one in a network. The approach to answer this question is usually called trust inference. In this paper, we propose a new trust inference algorithm (Called RN-Trust) based on the resistive networks concept. The algorithm, in addition to being simple, resolves some problems of previously proposed approaches. The analysis of the algorithm demonstrates that RN-Trust calculates the trust values more accurately than previous approaches.