分类
中间性中心性
中心性
聚类系数
节点(物理)
聚类分析
网络拓扑
数学
亲密度
计算机科学
拓扑(电路)
复杂网络
物理
组合数学
人工智能
计算机网络
统计
量子力学
万维网
数学分析
作者
Xing-Zhang Wen,Yue Zheng,Wenli Du,Zhuo-Ming Ren
标识
DOI:10.1016/j.chaos.2022.112880
摘要
The limitations of classical node centralities such as degree, closeness, betweenness and eigenvector are rooted in the network topology structure. For a deeper understanding, we regulate the basic network topology structure clustering and assortative coefficient to study the effect on these four classical node centralities. To observe the structural diversity of the complex network, we firstly construct two types of the growing scale-free networks with tunable clustering coefficient and assortative coefficient respectively, and simulate three types of null models on ten real networks to adjust cluster and assortativity. The results indicate that the impact of varying cluster and assortativity on node centrality in complex networks is obvious. We should pay more attention to the network topology when selecting node centralities as identifying the significance or influence of nodes in complex networks.
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