A Community-Based Approach to Identifying Influential Spreaders

Entropy

Zhiying Zhao³  Xiaofan Wang¹  Wei Zhang²  Zhiliang Zhu²  Guanrong Chen⁴  C.K. Michael Tse⁴  Mustak E. Yalcin⁴  Hai Yu⁴ 

[1] Department of Automation, Shanghai Jiao Tong University, Shanghai 200240, China; E-Mail:;Software College, Northeastern University, Shenyang 110819, China; E-Mail:;College of Information Science and Engineering, Northeastern University, Shenyang 110819, China E-Mail:;College of Information Science and Engineering, Northeastern University, Shenyang 110819, China E-Mail

关键词: influential spreaders;    community structure;    complex networks;   

DOI  :  10.3390/e17042228

来源: mdpi

【 摘 要 】

Identifying influential spreaders in complex networks has a significant impact on understanding and control of spreading process in networks. In this paper, we introduce a new centrality index to identify influential spreaders in a network based on the community structure of the network. The community-based centrality (CbC) considers both the number and sizes of communities that are directly linked by a node. We discuss correlations between CbC and other classical centrality indices. Based on simulations of the single source of infection with the Susceptible-Infected-Recovered (SIR) model, we find that CbC can help to identify some critical influential nodes that other indices cannot find. We also investigate the stability of CbC.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland