20 years of network community detection

被引：112

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

页码：848 / 850

页数：3

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