Network Growth Models

Network Growth Models is a theoretical framework in network science that specifies the mechanisms by which nodes and edges are incrementally added to a network over time, distinguished from other network models by its explicit emphasis on growth dynamics and preferential attachment processes that generate scale-free topologies.

709

Publications

85.4K

Citations

1.6K

Authors

731

Institutions

Publications per year

2017–2026

113

Authors

1.6K

  1. PL
    P. L. Krapivsky

    Boston University, United States

    16 publications · 3.2K citations

    15

    h-index

  2. SN
    S. N. Dorogovt︠s︡ev

    Physico-Technical Institute, Russia

    16 publications · 6K citations

    14

    h-index

  3. JF
    J. F. F. Mendes

    University of Aveiro, Portugal

    14 publications · 6K citations

    13

    h-index

  4. SR
    S. Redner

    Boston University, United States

    11 publications · 2.9K citations

    11

    h-index

  5. GC
    Guido Caldarelli

    IMT School for Advanced Studies Lucca, Italy

    10 publications · 1.4K citations

    10

    h-index

1–5 of 1.6K

Venues

  1. Physical Review E

    PRE · 82 publications · 4.9K citations

    35

    h-index

  2. Physical Review Letters

    PRL · 23 publications · 8.4K citations

    23

    h-index

  3. 21

    h-index

  4. Europhysics Letters (EPL)

    26 publications · 2.2K citations

    18

    h-index

  5. Scientific Reports

    22 publications · 994 citations

    16

    h-index

1–5