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

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 combine...

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Main Authors: Mukhtar, Mohd Fariduddin, Abal Abas, Zuraida, Baharuddin, Azhari Samsu, Norizan, Mohd Natashah, Wan Fakhruddin, Wan Farah Wani, Minato, Wakisaka, Abdul Rasib, Amir Hamzah, Abidin, Zaheera Zainal, Abdul Rahman, Ahmad Fadzli Nizam, Hairol Anuar, Siti Haryanti
Format: Article
Language:English
Published: Nature Research 2023
Online Access:http://psasir.upm.edu.my/id/eprint/108701/1/Integrating%20local%20and%20global%20information.pdf
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spelling oai:psasir.upm.edu.my:108701 http://psasir.upm.edu.my/id/eprint/108701/ Integrating local and global information to identify influential nodes in complex networks Mukhtar, Mohd Fariduddin Abal Abas, Zuraida Baharuddin, Azhari Samsu Norizan, Mohd Natashah Wan Fakhruddin, Wan Farah Wani Minato, Wakisaka Abdul Rasib, Amir Hamzah Abidin, Zaheera Zainal Abdul Rahman, Ahmad Fadzli Nizam Hairol Anuar, Siti Haryanti 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. Nature Research 2023-07-14 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/108701/1/Integrating%20local%20and%20global%20information.pdf 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 https://www.nature.com/articles/s41598-023-37570-7?error=cookies_not_supported&code=a0fae67a-1037-4ee2-87c4-7addcf6b6c76 10.1038/s41598-023-37570-7
institution UPM IR
collection UPM IR
language English
description 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.
format Article
author Mukhtar, Mohd Fariduddin
Abal Abas, Zuraida
Baharuddin, Azhari Samsu
Norizan, Mohd Natashah
Wan Fakhruddin, Wan Farah Wani
Minato, Wakisaka
Abdul Rasib, Amir Hamzah
Abidin, Zaheera Zainal
Abdul Rahman, Ahmad Fadzli Nizam
Hairol Anuar, Siti Haryanti
spellingShingle Mukhtar, Mohd Fariduddin
Abal Abas, Zuraida
Baharuddin, Azhari Samsu
Norizan, Mohd Natashah
Wan Fakhruddin, Wan Farah Wani
Minato, Wakisaka
Abdul Rasib, Amir Hamzah
Abidin, Zaheera Zainal
Abdul Rahman, Ahmad Fadzli Nizam
Hairol Anuar, Siti Haryanti
Integrating local and global information to identify influential nodes in complex networks
author_facet Mukhtar, Mohd Fariduddin
Abal Abas, Zuraida
Baharuddin, Azhari Samsu
Norizan, Mohd Natashah
Wan Fakhruddin, Wan Farah Wani
Minato, Wakisaka
Abdul Rasib, Amir Hamzah
Abidin, Zaheera Zainal
Abdul Rahman, Ahmad Fadzli Nizam
Hairol Anuar, Siti Haryanti
author_sort Mukhtar, Mohd Fariduddin
title Integrating local and global information to identify influential nodes in complex networks
title_short Integrating local and global information to identify influential nodes in complex networks
title_full Integrating local and global information to identify influential nodes in complex networks
title_fullStr Integrating local and global information to identify influential nodes in complex networks
title_full_unstemmed Integrating local and global information to identify influential nodes in complex networks
title_sort integrating local and global information to identify influential nodes in complex networks
publisher Nature Research
publishDate 2023
url http://psasir.upm.edu.my/id/eprint/108701/1/Integrating%20local%20and%20global%20information.pdf
_version_ 1819301821076733952
score 13.4562235

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