Citation
Mukhtar, Mohd Fariduddin and Abal Abas, Zuraida and Baharuddin, Azhari Samsu and Norizan, Mohd Natashah and Wan Fakhruddin, Wan Farah Wani and Minato, Wakisaka and Abdul Rasib, Amir Hamzah and Abidin, Zaheera Zainal and Abdul Rahman, Ahmad Fadzli Nizam and Hairol Anuar, Siti Haryanti
(2023)
Integrating local and global information to identify influential nodes in complex networks.
Scientific Reports, 13 (1).
art. no. 11411.
pp. 1-12.
ISSN 2045-2322
Abstract
Centrality analysis is a crucial tool for understanding the role of nodes in a network, but it is unclear how different centrality measures provide much unique information. To improve the identification of influential nodes in a network, we propose a new method called Hybrid-GSM (H-GSM) that combines the K-shell decomposition approach and Degree Centrality. H-GSM characterizes the impact of nodes more precisely than the Global Structure Model (GSM), which cannot distinguish the importance of each node. We evaluate the performance of H-GSM using the SIR model to simulate the propagation process of six real-world networks. Our method outperforms other approaches regarding computational complexity, node discrimination, and accuracy. Our findings demonstrate the proposed H-GSM as an effective method for identifying influential nodes in complex networks.
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