Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Virtual Community: Homesteading on the Electronic Frontier
Virtual Community: Homesteading on the Electronic Frontier
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
The Eigentrust algorithm for reputation management in P2P networks
WWW '03 Proceedings of the 12th international conference on World Wide Web
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximum independent set and related problems, with applications
Maximum independent set and related problems, with applications
Computing and applying trust in web-based social networks
Computing and applying trust in web-based social networks
Machine Learning
Identifying sets of key players in a social network
Computational & Mathematical Organization Theory
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Cost-effective outbreak detection in networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
On the approximability of influence in social networks
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
The application of social network analysis to identify trust-based networks in construction
International Journal of Networking and Virtual Organisations
Efficient influence maximization in social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Scalable influence maximization for prevalent viral marketing in large-scale social networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
FOCS '10 Proceedings of the 2010 IEEE 51st Annual Symposium on Foundations of Computer Science
Scalable Influence Maximization in Social Networks under the Linear Threshold Model
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
Robust optimization of graph partitioning and critical node detection in analyzing networks
COCOA'10 Proceedings of the 4th international conference on Combinatorial optimization and applications - Volume Part I
Improving Recommender Systems by Incorporating Social Contextual Information
ACM Transactions on Information Systems (TOIS)
Complexity of the critical node problem over trees
Computers and Operations Research
The impact of online social networking on learning: a social integration perspective
International Journal of Networking and Virtual Organisations
Proceedings of the fifth ACM international conference on Web search and data mining
ISCC '12 Proceedings of the 2012 IEEE Symposium on Computers and Communications (ISCC)
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In recent years, social networks analysis has become a very active area of research. There has been a great focus of studying social networks in the area of graph theory. One important problem in social networks is the identification of the most influential actors which can be detected using different graph parameters. In this paper, we attempt to identify minimum sets of the most influential actors in trust social networks using weighted graphs with more focus on the critical nodes detection. We propose three methods: the first identifies the sets of the most important critical nodes using the concept of network efficiency; the second specifies conditions under which critical nodes should be controlled using connected components; and the third extracts sets of most powerful articulation points which are able to play critical nodes role. Computational results are demonstrated to confirm the effectiveness of our methods.