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PageRank centrality for temporal networks
Authors:Laishui Lv  Kun Zhang  Ting Zhang  Dalal Bardou  Jiahui Zhang  Ying Cai
Institution:School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China
Abstract:In this paper, we propose a new centrality measure for ranking the nodes and time layers of temporal networks simultaneously, referred to as the f-PageRank centrality. The f-PageRank values of nodes and time layers in temporal networks are obtained by solving the eigenvector of a multi-homogeneous map. The existence and uniqueness of the proposed centrality measure are also guaranteed by existing results, under some reasonable conditions. The numerical experiments on a synthetic temporal network and two real-world temporal networks (i.e., Email-Eu-core and CollegeMsg temporal networks) show that the proposed centrality outperforms some existing centrality measures.
Keywords:Temporal networks  Centrality  PageRank  Transition probability tensors  Multi-homogeneous map
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