On the rich-club effect in dense and weighted networks
On the rich-club effect in dense and weighted networks
复制标题
DOI：
10.1140/epjb/e2009-00007-9
复制
发表时间：
2009-02-01
影响因子：
1.6
通讯作者：
Caldarelli, G.
中科院分区：
文献类型：
--
作者：
Zlatic, V.;Bianconi, G.;Caldarelli, G.
对于自然界中存在的许多复杂网络，只有一个实例，通常是大规模的，是可用的。在这个单一实例上进行的任何测量都不能在不同的实现上重复。为了检测真实世界网络中的重要模式，将测量结果与零模型对应物进行比较至关重要。在这里，我们专注于密集和加权网络，提出了一个合适的空模型，并研究了度相关性的行为，如富俱乐部系数所衡量的。我们的方法解决了一个现有的问题与稠密未加权图的随机化，并在同一时间代表了一个推广的丰富俱乐部系数加权网络，这是补充其他最近提出的。
For many complex networks present in nature only a single instance, usually of large size, is available. Any measurement made on this single instance cannot be repeated on different realizations. In order to detect significant patterns in a real-world network it is therefore crucial to compare the measured results with a null model counterpart. Here we focus on dense and weighted networks, proposing a suitable null model and studying the behaviour of the degree correlations as measured by the rich-club coefficient. Our method solves an existing problem with the randomization of dense unweighted graphs, and at the same time represents a generalization of the rich-club coefficient to weighted networks which is complementary to other recently proposed ones.