Multicores-periphery structure in networks

TL;DR

This paper introduces a new algorithm to identify multicores-periphery structures in networks, revealing complex layered connectivity patterns and outperforming existing methods in real-world network analysis.

Contribution

It defines the multicores-periphery structure and presents an algorithm for optimal partitioning, advancing network analysis techniques.

Findings

Successfully applied to social and patent networks

Revealed structural differences from existing algorithms

Enhanced understanding of network layered organization

Abstract

Many real-world networks exhibit a multicores-periphery structure, with densely connected vertices in multiple cores surrounded by a general periphery of sparsely connected vertices. Identification of the multicores-periphery structure can provide a new lens to understand the structures and functions of various real-world networks. This paper defines the multicores-periphery structure and introduces an algorithm to identify the optimal partition of multiple cores and the periphery in general networks. We demonstrate the performance of our algorithm by applying it to a well-known social network and a patent technology network, which are best characterized by the multicores-periphery structure. The analyses also reveal the differences between our multicores-periphery detection algorithm and two state-of-the-art algorithms for detecting the single core-periphery structure and community structure.