Community Detection

Community Detection is a computational method in network science that identifies densely connected subgroups within a larger network structure by distinguishing local clusters of nodes exhibiting stronger internal interactions compared to external ones.

4.2K

Publications

384.2K

Citations

9K

Authors

2.2K

Institutions

Publications per year

2017–2026

1.9K

Authors

9K

  1. DJ
    Di Jin

    Tianjin University, China

    46 publications · 2.4K citations

    27

    h-index

  2. ME
    M. E. J. Newman

    University of Michigan, United States

    28 publications · 41.9K citations

    26

    h-index

  3. DH
    Dongxiao He

    Tianjin University, China

    38 publications · 2K citations

    25

    h-index

  4. SF
    Santo Fortunato

    Institute for Scientific Interchange, Italy

    26 publications · 26.2K citations

    24

    h-index

  5. PS
    Philip S. Yu

    University of Illinois Chicago, United States

    29 publications · 2.2K citations

    21

    h-index

1–5 of 9K

Venues

  1. Physical Review E

    PRE · 116 publications · 64.2K citations

    67

    h-index

  2. Physica A Statistical Mechanics and its Applications

    203 publications · 10.2K citations

    49

    h-index

  3. arXiv (Cornell University)

    Repository · 186 publications · 7.6K citations

    45

    h-index

  4. PLoS ONE

    91 publications · 6.2K citations

    41

    h-index

  5. Information Sciences

    69 publications · 3.5K citations

    40

    h-index

1–5