Vital nodes identification in complex networks

被引:972
|
作者
Lu, Linyuan [1 ,2 ,3 ]
Chen, Duanbing [1 ,2 ,4 ]
Ren, Xiao-Long [5 ]
Zhang, Qian-Ming [4 ]
Zhang, Yi-Cheng [1 ,2 ,6 ]
Zhou, Tao [4 ]
机构
[1] Univ Elect Sci & Technol China, Inst Fundamental & Frontier Sci, Chengdu 610054, Peoples R China
[2] Univ Elect Sci & Technol China, Big Data Res Ctr, Chengdu 610054, Peoples R China
[3] Hangzhou Normal Univ, Alibaba Res Ctr Complex Sci, Hangzhou 310036, Zhejiang, Peoples R China
[4] Univ Elect Sci & Technol China, CompleX Lab, Web Sci Ctr, Chengdu 611731, Peoples R China
[5] Swiss Fed Inst Technol, Dept Humanities Social & Polit Sci, CH-8092 Zurich, Switzerland
[6] Univ Fribourg, Dept Phys, CH-1700 Fribourg, Switzerland
基金
中国国家自然科学基金; 瑞士国家科学基金会;
关键词
Complex networks; Vital nodes; Centrality; Message passing theory; Epidemic spreading; Percolation; IDENTIFYING INFLUENTIAL NODES; PREDICTING EMPLOYEE TURNOVER; PROTEIN-PROTEIN INTERACTION; SCALE-FREE NETWORKS; HETEROGENEOUS NETWORKS; BOOTSTRAP PERCOLATION; COMMUNITY STRUCTURE; SOCIAL NETWORK; H-INDEX; CENTRALITY;
D O I
10.1016/j.physrep.2016.06.007
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Real networks exhibit heterogeneous nature with nodes playing far different roles in structure and function. To identify vital nodes is thus very significant, allowing us to control the outbreak of epidemics, to conduct advertisements for e-commercial products, to predict popular scientific publications, and so on. The vital nodes identification attracts increasing attentions from both computer science and physical societies, with algorithms ranging from simply counting the immediate neighbors to complicated machine learning and message passing approaches. In this review, we clarify the concepts and metrics, classify the problems and methods, as well as review the important progresses and describe the state of the art. Furthermore, we provide extensive empirical analyses to compare well-known methods on disparate real networks, and highlight the future directions. In spite of the emphasis on physics-rooted approaches, the unification of the language and comparison with cross-domain methods would trigger interdisciplinary solutions in the near future. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:1 / 63
页数:63
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