A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition

doi:10.1142/S0217979221502519

	A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition
	Lu, Pengli 1; Zhang, Zhiru 1; Guo, Yuhong 3; Chen, Yahong 2
刊名	INTERNATIONAL JOURNAL OF MODERN PHYSICS B
	2021-09-30
卷号	35 期号:24
关键词	Complex networks minimum weighted degree decomposition local influentiality global influence capability susceptible-infected-recovered (SIR) model
ISSN号	0217-9792
DOI	10.1142/S0217979221502519
英文摘要	It has theoretical interest and practical significance to find out influential nodes which make the information spread faster and more extensive in complex networks. A variety of centrality measures have been proposed to identify influential nodes, while numerous of them are one-sided and may lead to inaccurate for identification. To overcome this issue, based on the defined minimum weighted degree decomposition, we propose a novel centrality method for identifying influential nodes by combining the local and global information. First, considering the local topological attribute of node and spread characteristic of neighbor nodes, the local influentiality is defined as the node's influence in the local range. Then, a weighted neighborhood coreness centrality is presented as the node's global influence capability by taking into account the potential impact of edges on information dissemination among nodes and position characteristic of node. Finally, taking the combinatorial centrality of local and global range as the final influence of node is more comprehensive and universally applicable. We use Susceptible-Infected-Recovered (SIR) model, monotonicity, Kendall's tau correlation coefficient and imprecision function to estimate the performance of our method. Comparison experiments conducted on 14 real-world networks indicate the effectiveness of the proposed method.
WOS研究方向	Physics
语种	英语
出版者	WORLD SCIENTIFIC PUBL CO PTE LTD
WOS记录号	WOS:000704763000007
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/149956]
专题	马克思主义学院
作者单位	1.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China; 2.Lishui Univ, Dept Math, Lishui 323000, Zhejiang, Peoples R China 3.Hexi Univ, Sch Math & Stat, Zhangye 734000, Gansu, Peoples R China;
推荐引用方式 GB/T 7714	Lu, Pengli,Zhang, Zhiru,Guo, Yuhong,et al. A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition[J]. INTERNATIONAL JOURNAL OF MODERN PHYSICS B,2021,35(24).
APA	Lu, Pengli,Zhang, Zhiru,Guo, Yuhong,&Chen, Yahong.(2021).A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition.INTERNATIONAL JOURNAL OF MODERN PHYSICS B,35(24).
MLA	Lu, Pengli,et al."A novel centrality measure for identifying influential nodes based on minimum weighted degree decomposition".INTERNATIONAL JOURNAL OF MODERN PHYSICS B 35.24(2021).