Profiling core-periphery network structure by random walkers

TLDR

Disclosing the main features of a network is crucial to understand static and dynamic properties such as robustness, spreading dynamics, and collective behaviours, and the core‑periphery paradigm models a network as a dense core and sparsely connected periphery highlighting node roles based on topology. The study demonstrates that a random‑walker approach can profile core‑periphery structure. The method assigns a coreness value to each node, thereby quantifying its position and role within the core‑periphery structure. The approach yields a core‑periphery profile curve and a numerical indicator that, when applied to diverse networks, reveal the overall structure and the distinctive roles of specific nodes.

Abstract

Disclosing the main features of the structure of a network is crucial to understand a number of static and dynamic properties, such as robustness to failures, spreading dynamics, or collective behaviours. Among the possible characterizations, the core-periphery paradigm models the network as the union of a dense core with a sparsely connected periphery, highlighting the role of each node on the basis of its topological position. Here we show that the core-periphery structure can effectively be profiled by elaborating the behaviour of a random walker. A curve—the core-periphery profile—and a numerical indicator are derived, providing a global topological portrait. Simultaneously, a coreness value is attributed to each node, qualifying its position and role. The application to social, technological, economical and biological networks reveals the power of this technique in disclosing the overall network structure and the peculiar role of some specific nodes.