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

ABSTRACT: Centrality is widely recognized as one of the most critical measures to provide insight into the structure and function of complex networks. While various centrality measures have been proposed for single-layer networks, a general framework for studying centrality in multilayer networks (i.e., multicentrality) is still lacking. In this study, a tensor-based framework is introduced to study eigenvector multicentrality, which enables the quantification of the impact of interlayer influence on multicentrality, providing a systematic way to describe how multicentrality propagates across different layers. This framework can leverage prior knowledge about the interplay among layers to better characterize multicentrality for varying scenarios. Two interesting cases are presented to illustrate how

SUBMITTER: Wu M 

PROVIDER: S-EPMC6681706 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature