ArticlePloS one2019
Consistency and differences between centrality measures across distinct classes of networks.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.
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88 citing papers in PubMed.
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- Temporal invariance of centrality correlations and hierarchical topology in evolving cross-shareholding networks in Japan (2001-2023).PloS one · 2026Article
- Connectivity of the adult human brain with sequential neurogenesis of circuits and transcriptomics signatures.Nature communications · 2025Article
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- Identifying influential assets in higher order interdependent infrastructure networks through population impact.Scientific reports · 2025Article
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- Support of Underrepresented and Early-Stage Faculty at a Research Center for Minority Institutions: A Social Network Analysis of Research Productivity over a Five-Year Period.Innovative higher education · 2025Article
- The different impacts of functional network centrality and connectivity on the complexity of brain signals in healthy control and first-episode drug-naïve patients with major depressive disorder.Brain imaging and behavior · 2025Article
- A novel approach for target deconvolution from phenotype-based screening using knowledge graph.Scientific reports · 2025Article
- The impact of physical activity and dietary behavior on depression in college students: a study on mediation effects and network analysis.Frontiers in public health · 2025Article
- A simulated annealing algorithm for randomizing weighted networks.Nature computational science · 2025Article
- Central and Peripheral People in a Social Representation Network.International review of social psychology · 2025Article
- Phylogenomic and synteny analysis of BAHD and SCP/SCPL gene families reveal their evolutionary histories in plant specialized metabolism.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Distribution of centrality measures on undirected random networks via the cavity method.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
28 more citing papers are in PubMed but not listed here.
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The roles of different nodes within a network are often understood through centrality analysis, which aims to quantify the capacity of a node to influence, or be influenced by, other nodes via its connection topology. Many different centrality measures have been proposed, but the degree to which they offer unique information, and whether it is advantageous to use multiple centrality measures to define node roles, is unclear. Here we calculate correlations between 17 different centrality measures across 212 diverse real-world networks, examine how these correlations relate to variations in network density and global topology, and investigate whether nodes can be clustered into distinct classes according to their centrality profiles. We find that centrality measures are generally positively correlated to each other, the strength of these correlations varies across networks, and network modularity plays a key role in driving these cross-network variations. Data-driven clustering of nodes based on centrality profiles can distinguish different roles, including topological cores of highly central nodes and peripheries of less central nodes. Our findings illustrate how network topology shapes the pattern of correlations between centrality measures and demonstrate how a comparative approach to network centrality can inform the interpretation of nodal roles in complex networks.
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