Influential nodes identification in complex networks based on global and local information  

作　　者：Yuan-Zhi Yang Min Hu Tai-Yu Huang 杨远志;胡敏;黄泰愚(Air Force Engineering University,Xi'an 710038,China;China Petroleum Planning and Engineering Institute,Beijing 100083,China;Sichuan University of Arts and Science,Dazhou 635000,China)

机构地区：[1]Air Force Engineering University,Xi'an 710038,China [2]China Petroleum Planning and Engineering Institute,Beijing 100083,China [3]Sichuan University of Arts and Science,Dazhou 635000,China

出　　处：《Chinese Physics B》2020年第8期572-578,共7页中国物理B（英文版）

摘　　要：Identifying influential nodes in complex networks is essential for network robust and stability,such as viral marketing and information control.Various methods have been proposed to define the influence of nodes.In this paper,we comprehensively consider the global position and local structure to identify influential nodes.The number of iterations in the process of k-shell decomposition is taken into consideration,and the improved k-shell decomposition is then put forward.The improved k-shell decomposition and degree of target node are taken as the benchmark centrality,in addition,as is well known,the effect between node pairs is inversely proportional to the shortest path length between two nodes,and then we also consider the effect of neighbors on target node.To evaluate the performance of the proposed method,susceptible-infected(SI)model is adopted to simulate the spreading process in four real networks,and the experimental results show that the proposed method has obvious advantages over classical centrality measures in identifying influential nodes.

关 键 词：complex networks influential nodes global position local structure susceptible-infected(SI)model 

分 类 号：O157.5[理学—数学]