Journal
EUROPEAN PHYSICAL JOURNAL B
Volume 67, Issue 3, Pages 271-275Publisher
SPRINGER
DOI: 10.1140/epjb/e2009-00007-9
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Funding
- Generalitat de Catalunya [2006PIV0001]
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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.
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