Subgraph centrality and clustering in complex hyper-networks
Subgraph centrality and clustering in complex hyper-networks
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DOI：
10.1016/j.physa.2005.12.002
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发表时间：
2006-05-15
影响因子：
3.3
通讯作者：
Rodríguez-Velázquez, JA
中科院分区：
文献类型：
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作者：
Estrada, E;Rodríguez-Velázquez, JA
将复杂系统表示为网络是不适合研究某些问题的。我们展示了几个社会、生物、生态和技术系统的例子，在这些系统中，使用复杂网络提供的关于系统结构的信息非常有限。因此，我们将子图中心性和聚类性的概念推广到以超图表示的复杂网络：复杂超网络。第一个参数刻画了节点在不同子超图中的参与度，第二个参数通过超三角形与长度为2的路的比例来刻画超网络中的传递性。还介绍了在超网络中形成相互邻接群的三元组的另一种度量。所有这些特征都在三个不同的超网络中进行了研究：科学合作超网络、生态竞争超网络和1999年美国企业精英形成的超网络。(C)2006爱思唯尔B.V.保留所有权利。
The representation of complex systems as networks is inappropriate for the study of certain problems. We show several examples of social, biological, ecological and technological systems where the use of complex networks gives very limited information about the structure of the system. Consequently, we extend the concepts of subgraph centrality and clustering for complex networks represented by hypergraphs: complex hyper-networks. The first parameter characterizes the node participation in different sub-hypergraphs and the second one characterizes the transitivity in the hyper-network through the proportion of hyper-triangles to paths of length two. Another measure characterizing the formation of triples of mutually adjacent groups in the hyper-network is also introduced. All of these characteristics are studied in three different hyper-networks: a scientific collaboration hyper-network, an ecological competition hyper-network and the hyper-network formed by the American corporate elite in 1999. (c) 2006 Elsevier B.V. All rights reserved.