Aug 2026· SN Computer Science· Vol 7· 0 citations· 53 references
TL;DR
Experimental results in seven complex networks of the real world show that the proposed hybrid centrality called k-core neighborhood density (KND) remarkably balances rank distribution and accuracy, and the identified influential nodes have a superior ability to spread their influence over a wide area of a network.
This study introduces a new ranking framework that integrates a quasi-Laplacian structural measure with a gravity-inspired aggregation process and demonstrates that the proposed framework consistently outperforms existing techniques in terms of accuracy, resolution, and computational simplicity.
Shima Esfandiari, S. M. Fakhrahmad· arXiv.org· 0 citations
Identifying influential nodes in complex networks is a fundamental problem with applications in information diffusion, epidemic control, infrastructure robustness, and biological systems. Traditional approaches rely on structural centrality measures, such as degree, betweenness, closeness, and PageRank, which quantify...
A. Kurudi̇rek, Ibrahim Filik, Sravan Sakhamuri et al.· 2026 International Conferenc...· 0 citations
Comprehensive evaluations on multiple real-world networks demonstrate KSvoterank’s superior performance in propagation scope and robustness, validating its utility for influence maximization and network robustness analysis.
Hai-Long Chen, Jiafei Liu, Eddie Cheng· International Journal of Mac...· 0 citations
WKDH fuses local structural attributes with global structural attributes via a multiplicative weighted synergy model, simultaneously capturing local connection “quantity,” local connection “quality,” and global core-layer position, and achieves linear computational complexity of O(m).
Na Zhao, Chaozhou Dai, Guo-Lin Yang et al.· Entropy· 0 citations
Spectral Efficiency Centrality (SEC), a temporal spectral centrality framework that quantifies node importance by evaluating the change in spectral radius caused by node removal across temporal snapshots, and ASEC, an efficient approximation based on Perron-Frobenius theory and first-order eigenvalue perturbation that...
A novel heuristic community detection algorithm, termed CoDeSEG, which identifies communities by minimizing the network's two-dimensional structural entropy within a potential game framework, and introduces a structural entropy-based node overlapping heuristic for detecting overlapping communities, with a near-linear t...
Pu Li, Yantuan Xian, Hao Peng et al.· arXiv.org· 0 citations
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