Coreness Tunable Network Model

Abstract

Kitsak et al argued that nodes dwell in diverse network shells by a k-core decomposition process show more reliable identification for nodal importance which had attracted more and more attentions in different domains. But one seldom focuses on the distribution of node numbers (DNN) in different shells of a network, experiment results show regular characteristics. While, the existing theoretical network models, such as BA scale-free model, WS Small-world model, ER random network model et al cannot reproduce the features. To fill this gap, a group of coreness tunable network (CTN) models are proposed, in which the coreness of each node is totally controllable. The CTN has a similar network performance compared to real-world by counting basic static geometric features and spreading performance under SIR model. Our CTN models are providing a theoretical framework to deepen humans’ understanding of the coreness structure and function of complex networks.