Open Physics | |
Research on Critical Nodes Algorithm in Social Complex Networks | |
Wang Xue-Guang1  | |
[1] Department of Computer Science, East China University of Political Science and Law, Shanghai201620, China; | |
关键词: critical node problem; complex networks; community structure; influence maximization; 01.20.+x; 07.05.mh; | |
DOI : 10.1515/phys-2017-0008 | |
来源: DOAJ |
【 摘 要 】
Discovering critical nodes in social networks has many important applications and has attracted more and more institutions and scholars. How to determine the K critical nodes with the most influence in a social network is a NP (define) problem. Considering the widespread community structure, this paper presents an algorithm for discovering critical nodes based on two information diffusion models and obtains each node’s marginal contribution by using a Monte-Carlo method in social networks. The solution of the critical nodes problem is the K nodes with the highest marginal contributions. The feasibility and effectiveness of our method have been verified on two synthetic datasets and four real datasets.
【 授权许可】
Unknown