2017/04/11 by Alessandro Muscoloni, Muscoloni, Alessandro, Carlo Vittorio Cannistraci +1
Neuroscience · Physics and Astronomy · #Complex Network Analysis Techniques #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Functional Brain Connectivity Studies #Opinion Dynamics and Social Influence #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.1704.03526
openalex publication_date 2017/04/11 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28
The rich-club concept has been introduced in order to characterize the\npresence of a cohort of nodes with a large number of links (rich nodes) that\ntend to be well connected between each other, creating a tight group (club).\nRich-clubness defines the extent to which a network displays a topological\norganization characterized by the presence of a node rich-club. It is crucial\nfor the investigation of internal organization and function of networks arising\nin systems of disparate fields such as transportation, social, communication\nand neuroscience. Different methods have been proposed for assessing the\nrich-clubness and various null-models have been adopted for performing\nstatistical tests. However, a procedure that assigns a unique value of\nrich-clubness significance to a given network is still missing. Our solution to\nthis problem grows on the basis of three new pillars. We introduce: i) a\nnull-model characterized by a lower rich-club coefficient; ii) a fair strategy\nto normalize the level of rich-clubness of a network in respect to the\nnull-model; iii) a statistical test that, exploiting the maximum deviation of\nthe normalized rich-club coefficient attributes a unique p-value of\nrich-clubness to a given network. In conclusion, this study proposes the first\nattempt to quantify, using a unique measure, whether a network presents a\nsignificant rich-club topological organization. The general impact of our study\non engineering and science is that simulations investigating how the functional\nperformance of a network is changing in relation to rich-clubness might be more\neasily tuned controlling one unique value: the proposed rich-clubness measure.\n