Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization

doi:10.1016/j.physa.2018.09.040

	Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization
	Tang, Jianxin 1,2; Zhang, Ruisheng 1; Yao, Yabing 1; Yang, Fan 1; Zhao, Zhili 1; Hu, Rongjing 1; Yuan, Yongna 1
刊名	PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
	2019-01
卷号	513 页码:477-496
关键词	Social networks Influence maximization Metaheuristic Discrete particle swarm optimization Local search strategy
ISSN号	0378-4371
DOI	10.1016/j.physa.2018.09.040
英文摘要	Influence maximization aims to select a subset of top-k influential nodes to maximize the influence propagation, and it remains an open research topic of viral marketing and social network analysis. Submodularity-based methods including greedy algorithm can provide solutions with performance guarantee, but the time complexity is unbearable especially in large-scale networks. Meanwhile, conventional centrality-based measures cannot provide steady performance for multiple influential nodes identification. In this paper, we propose an improved discrete particle swarm optimization with an enhanced network topology based strategy for influence maximization. According to the strategy, the k influential nodes in a temporary optimal seed set are recombined firstly in ascending order by degree metric to let the nodes with lower degree centrality exploit more influential neighbors preferentially. Secondly, a local greedy strategy is applied to replace the current node with the most influential node from the direct neighbor set of each node from the temporary seed set. The experimental results conducted in six social networks under independent cascade model show that the proposed algorithm outperforms typical centrality-based heuristics, and achieves comparable results to greedy algorithm but with less time complexity. (C) 2018 Elsevier B.V. All rights reserved.
资助项目	Fundamental Research Funds for the Central Universities, China[lzujbky-2017-191]
WOS研究方向	Physics
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000448496200044
状态	已发表
内容类型	期刊论文
源URL	[http://119.78.100.223/handle/2XXMBERH/32227]
专题	计算机与通信学院
通讯作者	Zhang, Ruisheng
作者单位	1.Lanzhou Univ, Sch Informat Sci & Engn, Lanzhou 730000, Gansu, Peoples R China 2.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
推荐引用方式 GB/T 7714	Tang, Jianxin,Zhang, Ruisheng,Yao, Yabing,et al. Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization[J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,2019,513:477-496.
APA	Tang, Jianxin.,Zhang, Ruisheng.,Yao, Yabing.,Yang, Fan.,Zhao, Zhili.,...&Yuan, Yongna.(2019).Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization.PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS,513,477-496.
MLA	Tang, Jianxin,et al."Identification of top-k influential nodes based on enhanced discrete particle swarm optimization for influence maximization".PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 513(2019):477-496.