Prof. HE Shibo's Group published an article about multilayer networks in PNAS

Recently, Professor HE Shibo’s research group published an article about multilayer networks in Proceedings of the National Academy of Sciences of the United States of America (PNAS): A tensor-based framework for studying eigenvector multicentrality in multilayer networks.

WU Mincheng, the first author, is a doctoral student at Zhejiang University. The research is led by the ZJU State Key Lab of Industrial Control Technology, jointly completed by Princeton University and other international research institutions.

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 to model multilayer influence by choosing appropriate functions of interlayer influence and design algorithms to calculate eigenvector multicentrality. This framework is applied to analyze several empirical multilayer networks, and the results corroborate that it can quantify the influence among layers and multicentrality of nodes effectively.

To Read the Full Article: 

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

Reporter: REN Tong

Editor: WANG Jing