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...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Springer Nature
2023
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| Subjects: | |
| Online Access: | http://eprints.utm.my/106849/1/WanFarahWani2023_IntegratingLocalandGlobalInformationtoIdentify.pdf |
| _version_ | 1811132423783579648 |
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| author | Mukhtar, Mohd. Fariduddin Abas, Zuraida Abal Samsu Baharuddin, Azhari Norizan, Mohd. Natashah Wan Fakhruddin, Wan Farah Wani Minato, Wakisaka Abdul Rasib, Amir Hamzah Zainal Abidin, Zaheera Abdul Rahman, Ahmad Fadzli Nizam Hairol Anuar, Siti Haryanti |
| author_facet | Mukhtar, Mohd. Fariduddin Abas, Zuraida Abal Samsu Baharuddin, Azhari Norizan, Mohd. Natashah Wan Fakhruddin, Wan Farah Wani Minato, Wakisaka Abdul Rasib, Amir Hamzah Zainal Abidin, Zaheera Abdul Rahman, Ahmad Fadzli Nizam Hairol Anuar, Siti Haryanti |
| author_sort | Mukhtar, Mohd. Fariduddin |
| collection | ePrints |
| 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. |
| first_indexed | 2024-09-24T00:03:54Z |
| format | Article |
| id | utm.eprints-106849 |
| institution | Universiti Teknologi Malaysia - ePrints |
| language | English |
| last_indexed | 2024-09-24T00:03:54Z |
| publishDate | 2023 |
| publisher | Springer Nature |
| record_format | dspace |
| spelling | utm.eprints-1068492024-08-01T05:32:43Z http://eprints.utm.my/106849/ Integrating local and global information to identify influential nodes in complex networks Mukhtar, Mohd. Fariduddin Abas, Zuraida Abal Samsu Baharuddin, Azhari Norizan, Mohd. Natashah Wan Fakhruddin, Wan Farah Wani Minato, Wakisaka Abdul Rasib, Amir Hamzah Zainal Abidin, Zaheera Abdul Rahman, Ahmad Fadzli Nizam Hairol Anuar, Siti Haryanti H Social Sciences (General) Q Science (General) 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. Springer Nature 2023-07-14 Article PeerReviewed application/pdf en http://eprints.utm.my/106849/1/WanFarahWani2023_IntegratingLocalandGlobalInformationtoIdentify.pdf Mukhtar, Mohd. Fariduddin and Abas, Zuraida Abal and Samsu Baharuddin, Azhari 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 influential nodes in complex networks. Scientific Reports, 13 (1). pp. 1-12. ISSN 2045-2322 http://dx.doi.org/10.1038/s41598-023-37570-7 DOI:10.1038/s41598-023-37570-7 |
| spellingShingle | H Social Sciences (General) Q Science (General) Mukhtar, Mohd. Fariduddin Abas, Zuraida Abal Samsu Baharuddin, Azhari Norizan, Mohd. Natashah Wan Fakhruddin, Wan Farah Wani Minato, Wakisaka Abdul Rasib, Amir Hamzah Zainal Abidin, Zaheera Abdul Rahman, Ahmad Fadzli Nizam Hairol Anuar, Siti Haryanti Integrating local and global information to identify influential nodes in complex networks |
| title | 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_short | 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 |
| topic | H Social Sciences (General) Q Science (General) |
| url | http://eprints.utm.my/106849/1/WanFarahWani2023_IntegratingLocalandGlobalInformationtoIdentify.pdf |
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