A Community-Based Approach to Identifying Influential Spreaders
A Community-Based Approach to Identifying Influential Spreaders
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DOI：
10.3390/e17042228
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发表时间：
2015-04
期刊：
影响因子：
2.7
通讯作者：
Zhiying Zhao;X. Wang;Wei Zhang-;Zhiliang Zhu
中科院分区：
文献类型：
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作者：
Zhiying Zhao;X. Wang;Wei Zhang-;Zhiliang Zhu
识别复杂网络中有影响力的传播者对于理解和控制网络传播过程具有重要意义。在本文中，我们引入了一个新的中心性指标，以确定有影响力的传播者在网络的社区结构的基础上。基于社区的中心性（Community-based Centrality，CbC）考虑了由节点直接链接的社区的数量和大小。我们讨论了CbC和其他经典的中心性指标之间的相关性。基于对单一传染源的易感-感染-传播（SIR）模型的模拟，我们发现CbC可以帮助识别一些其他指标无法找到的关键影响节点。我们还研究了CbC的稳定性。
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.