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Detection of top-K central nodes in social networks: A compressive sensing approach
, Article Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015, 25 August 2015 through 28 August 2015 ; 2015 , Pages 902-909 ; 9781450338547 (ISBN) ; Pei, J ; Tang, J ; Silvestri, F ; Sharif University of Technology
Association for Computing Machinery, Inc
2015
Abstract
In analysing the structural organization of a social network, identifying important nodes has been a fundamental problem. The concept of network centrality deals with the assessment of the relative importance of a particular node within the network. Most of the traditional network centrality definitions have a high computational cost and require full knowledge of network topological structure. On the one hand, in many applications we are only interested in detecting the top-k central nodes of the network with the largest values considering a specific centrality metric. On the other hand, it is not feasible to efficiently identify central nodes in a large real-world social network via...