Multi-level community-based centrality integrating local-to-global information for identifying critical components

Yifan Wang, Ziyang Jin, Dongli Duan and Ning Wang

Physica A: Statistical Mechanics and its Applications, 2025, vol. 678, issue C

Abstract: The structural heterogeneity of complex networks across scales (local-to-global) results in critical components that disproportionately drive system functionality. Identifying and protecting critical components is of great theoretical and practical significance for ensuring the safe and efficient operation of complex systems. Recently, there has been a notable trend in applying centrality measures to identify critical components within networks. However, existing approaches rarely incorporate integrated multi-scale analysis, encompassing both local and global network properties. To fill this gap, this study proposed the Multi-level Community Structure Centrality (MCSC) method for identifying critical components. The MCSC approach employs a hierarchical community detection algorithm to capture multi-scale structural information. At each hierarchical level, the method evaluates component influence by incorporating community size, inter-community connection density, and adjacent components competition relationships. The effectiveness of the proposed method was evaluated through comprehensive testing on diverse real-world network datasets. The results demonstrate that MCSC performs well in terms of interpretability, identification accuracy, computational cost, and applicability, outperforming classical centrality measures in most networks.

Keywords: Complex network; Centrality; Community structure; Multi-scale (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437125006259
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:678:y:2025:i:c:s0378437125006259

DOI: 10.1016/j.physa.2025.130973

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().