A divide‐and‐conquer algorithm for core‐periphery identification in large networks

Core‐periphery structure is an important network feature where the network is broken into two components: a densely connected core and a loosely connected periphery. In this work, we propose a divide‐and‐conquer algorithm to identify the core‐periphery structure in large networks. By finding this st...

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Bibliographic Details
Published in:	Stat (International Statistical Institute) Vol. 11; no. 1
Main Author:	Yanchenko, Eric
Format:	Journal Article
Language:	English
Published:	01.12.2022
Subjects:	large and complex data sets networks statistical computing
ISSN:	2049-1573, 2049-1573
Online Access:	Get full text
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Summary:	Core‐periphery structure is an important network feature where the network is broken into two components: a densely connected core and a loosely connected periphery. In this work, we propose a divide‐and‐conquer algorithm to identify the core‐periphery structure in large networks. By finding this structure on much smaller sub‐samples of the network and then combining the results across sub‐samples, this method yields fast and accurate core‐periphery labels. Additionally, the method provides a measure of the statistical significance of the structure. We apply our approach to synthetic data to find the algorithm's detection limit and on a real‐world network with more than 35,000 nodes.
ISSN:	2049-1573 2049-1573
DOI:	10.1002/sta4.475