A modified efficiency centrality to identify influential nodes in weighted networks

Pramana: Journal of physics

YONG DENG^3,4,5²  SHASHA WANG^2³  YUNCHUAN WANG^1⁵ 

[1] Big Data Decision Institute, Jinan University, Guangzhou, China^4;Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China^3;School of Computer Science, Sichuan University, Chengdu, China^2;School of Computer and Information Science, Southwest University, Chongqing, China^5;School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China^1

关键词: Complex network;    influential nodes;    weighted network;    efficiency centrality;   

DOI  :  

学科分类：物理（综合）

来源: Indian Academy of Sciences

【 摘 要 】

It is still a crucial issue to identify influential nodes effectively in the study of complex networks. As for the existing efficiency centrality (EffC), it cannot be applied to a weighted network. In this paper, a modified efficiency centrality ($\rm{EffC}^{m}$) is proposed by extending EffC into weighted networks. The proposed measure trades off the node degree and global structure in a weighted network. The influence of both the sum of the average degree of nodes in the whole network and the average distance of the network is taken into account. Numerical examples are used to illustrate the efficiency of the proposed method.

【 授权许可】

CC BY