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A tensor-based framework for studying eigenvector multicentrality in multilayer networks

Author(s): Wu, Mincheng; He, Shibo; Zhang, Yongtao; Chen, Jiming; Sun, Youxian; et al

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dc.contributor.authorWu, Mincheng-
dc.contributor.authorHe, Shibo-
dc.contributor.authorZhang, Yongtao-
dc.contributor.authorChen, Jiming-
dc.contributor.authorSun, Youxian-
dc.contributor.authorLiu, Yang-Yu-
dc.contributor.authorZhang, Junshan-
dc.contributor.authorPoor, H Vincent-
dc.identifier.citationWu, Mincheng, He, Shibo, Zhang, Yongtao, Chen, Jiming, Sun, Youxian, Liu, Yang-Yu, Zhang, Junshan, Poor, H Vincent. (2019). A tensor-based framework for studying eigenvector multicentrality in multilayer networks. Proceedings of the National Academy of Sciences, 116 (31), 15407 - 15413. doi:10.1073/pnas.1801378116en_US
dc.description.abstractIt is of significant interest to understand the structure and function of multilayer networks, which model many practical complex systems. Centrality, quantifying the importance of nodes in a graph, is widely recognized as one of the most effective measures. Nevertheless, a general framework for characterizing centrality in multilayer networks is still lacking. In this article, we fill this gap by developing a tensor-based framework for characterizing eigenvector multicentrality in general multilayer networks. We prove the existence and uniqueness of eigenvector multicentrality for 2 interesting scenarios, using the proposed framework. The results from empirical networks demonstrate that this framework helps us obtain a clear understanding of the eigenvector multicentrality of nodes.en_US
dc.relation.ispartofProceedings of the National Academy of Sciencesen_US
dc.rightsAuthor's manuscripten_US
dc.titleA tensor-based framework for studying eigenvector multicentrality in multilayer networksen_US
dc.typeJournal Articleen_US

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