ArticleNature communications2024
DomiRank Centrality reveals structural fragility of complex networks via node dominance.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Critical nodes identification and cascading failure mitigation strategies in multi-layer coupled networks of interdependent critical infrastructures.Scientific reports · 2026Article
- Attention on social media depends more on how you express yourself than on who you are.Nature human behaviour · 2026Article
- The application of DM-MSTP method on Tunisian financial market: 2024 case study.Frontiers in artificial intelligence · 2026Article
- Graph convolutional network for modeling corridor-based urban transformation: Revealing spatial coherence in land-use change in Erbil.PloS one · 2026Article
- Climate-resilient railway networks: a resource-aware framework.Communications engineering · 2025Article
- A Method Inspired by One-Dimensional Discrete-Time Quantum Walks for Influential Node Identification.Entropy (Basel, Switzerland) · 2025Article
- Identifying Influential Nodes Based on Evidence Theory in Complex Network.Entropy (Basel, Switzerland) · 2025Article
- 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
- Identifying influential nodes based on the disassortativity and community structure of complex network.Scientific reports · 2024Article
- A Deep Differential Analysis in Four Subtypes of Breast Cancer Based on Regulations of miRNA-mRNA.IET systems biologyArticle
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Determining the key elements of interconnected infrastructure and complex systems is paramount to ensure system functionality and integrity. This work quantifies the dominance of the networks' nodes in their respective neighborhoods, introducing a centrality metric, DomiRank, that integrates local and global topological information via a tunable parameter. We present an analytical formula and an efficient parallelizable algorithm for DomiRank centrality, making it applicable to massive networks. From the networks' structure and function perspective, nodes with high values of DomiRank highlight fragile neighborhoods whose integrity and functionality are highly dependent on those dominant nodes. Underscoring this relation between dominance and fragility, we show that DomiRank systematically outperforms other centrality metrics in generating targeted attacks that effectively compromise network structure and disrupt its functionality for synthetic and real-world topologies. Moreover, we show that DomiRank-based attacks inflict more enduring damage in the network, hindering its ability to rebound and, thus, impairing system resilience. DomiRank centrality capitalizes on the competition mechanism embedded in its definition to expose the fragility of networks, paving the way to design strategies to mitigate vulnerability and enhance the resilience of critical infrastructures.
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.