20 years of network community detection

被引：85
作者：
Fortunato, Santo [1 ,2 ]
Newman, Mark E. J. [3 ,4 ]
机构：
[1] Indiana Univ, Network Sci Inst IUNI, Bloomington, IN 47408 USA
[2] Indiana Univ, Luddy Sch Informat Comp & Engn, Bloomington, IN 47408 USA
[3] Univ Michigan, Dept Phys, Ann Arbor, MI 48109 USA
[4] Univ Michigan, Ctr Study Complex Syst, Ann Arbor, MI 48109 USA
来源：
NATURE PHYSICS | 2022年 / 18卷 / 08期
基金：
美国国家科学基金会;
关键词：
COMPLEX NETWORKS;
D O I：
10.1038/s41567-022-01716-7
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
A fundamental technical challenge in the analysis of network data is the automated discovery of communities - groups of nodes that are strongly connected or that share similar features or roles. In this Comment we review progress in the field over the past 20 years.
引用
收藏
页码：848 / 850
页数：3
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