TY  - JOUR
AV  - none
N2  - 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. 
TI  - On the rich-club effect in dense and weighted networks
A1  - Zlatic, Vinko
A1  - Bianconi, Ginestra
A1  - Díaz-Guilera, Albert
A1  - Garlaschelli, Diego
A1  - Rao, Francesco
A1  - Caldarelli, Guido
SN  - 1434-6028
Y1  - 2009///
ID  - eprints1091
SP  - 271
IS  - 3
EP  - 275
JF  - The European Physical Journal B
UR  - http://dx.doi.org/10.1140/epjb/e2009-00007-9
KW  - PACS: 89.75.Hc Networks and genealogical trees; 89.75.Fb Structures and organization in complex systems 
VL  - 67
ER  -