A Community-Based Approach to Identifying Influential Spreaders
AbstractIdentifying 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. View Full-Text
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Zhao, Z.; Wang, X.; Zhang, W.; Zhu, Z. A Community-Based Approach to Identifying Influential Spreaders. Entropy 2015, 17, 2228-2252.
Zhao Z, Wang X, Zhang W, Zhu Z. A Community-Based Approach to Identifying Influential Spreaders. Entropy. 2015; 17(4):2228-2252.Chicago/Turabian Style
Zhao, Zhiying; Wang, Xiaofan; Zhang, Wei; Zhu, Zhiliang. 2015. "A Community-Based Approach to Identifying Influential Spreaders." Entropy 17, no. 4: 2228-2252.