Integrating local and global information to identify infuential nodes in complex networks

Abal Abas, Zuraida and Baharuddin, Azhari Samsu and Mukhtar, Mohd Fariduddin and Norizan, Mohd Natashah and Wan Fakhruddin, Wan Farah Wani and Minato, Wakisaka and Abdul Rasib, Amir Hamzah and Zainal Abidin, Zaheera and Abdul Rahman, Ahmad Fadzli Nizam and Hairol Anuar, Siti Haryanti (2023) Integrating local and global information to identify infuential nodes in complex networks. Scientific Reports, 13 (1). pp. 1-12. ISSN 2045-2322

Text 0235418072023246.PDF Download (3MB)

Abstract

Centrality analysis is a crucial tool for understanding the role of nodes in a network, but it is unclear how diferent centrality measures provide much unique information. To improve the identifcation of infuential 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 fndings demonstrate the proposed H-GSM as an efective method for identifying infuential nodes in complex networks.

Item Type:	Article
Uncontrolled Keywords:	Identify infuential nodes, Hybrid-GSM (H-GSM), Global Structure Model (GSM), Complex networks
Divisions:	Faculty Of Mechanical Technology And Engineering
Depositing User:	Norfaradilla Idayu Ab. Ghafar
Date Deposited:	04 Jul 2024 11:30
Last Modified:	04 Jul 2024 11:30
URI:	http://eprints.utem.edu.my/id/eprint/27566
Statistic Details:	View Download Statistic

Actions (login required)

View Item