Soffer Sara Nadiv, Vázquez Alexei
Department of Mathematics, Rutgers University Piscataway, New Jersey 08854, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2005 May;71(5 Pt 2):057101. doi: 10.1103/PhysRevE.71.057101. Epub 2005 May 13.
The clustering coefficient quantifies how well connected are the neighbors of a vertex in a graph. In real networks it decreases with the vertex degree, which has been taken as a signature of the network hierarchical structure. Here we show that this signature of hierarchical structure is a consequence of degree-correlation biases in the clustering coefficient definition. We introduce a definition in which the degree-correlation biases are filtered out, and provide evidence that in real networks the clustering coefficient is constant or decays logarithmically with vertex degree.
聚类系数量化了图中一个顶点的邻接点之间的连接程度。在实际网络中,它会随着顶点度的增加而减小,这一点已被视为网络层次结构的一个特征。在这里,我们表明这种层次结构的特征是聚类系数定义中度数关联偏差的结果。我们引入了一种滤除度数关联偏差的定义,并提供证据表明在实际网络中,聚类系数是恒定的,或者随着顶点度呈对数衰减。