Large-scale Community Visualization

Large-Scale Community Visualization is a computational visualization framework that enables the representation and analysis of community structures in large-scale networks by integrating scalable algorithms with interactive visual analytics to reveal hierarchical, overlapping, or evolving community patterns across massive graph datasets.

22

Publications

2.2K

Citations

84

Authors

40

Institutions

Publications per year

2017–2026

5

Authors

84

  1. AJ
    Agma J. M. Traina

    Universidade de São Paulo, Brazil

    2 publications · 62 citations

    2

    h-index

  2. CF
    Christos Faloutsos

    Carnegie Mellon University, United States

    2 publications · 62 citations

    2

    h-index

  3. DB
    danah boyd

    Microsoft (United States), United States

    2 publications · 723 citations

    2

    h-index

  4. JF
    José F. Rodrigues

    Universidade de São Paulo, Brazil

    2 publications · 62 citations

    2

    h-index

  5. JH
    Jeffrey Heer

    University of Washington, United States

    2 publications · 723 citations

    2

    h-index

1–5 of 84

Venues

  1. Bioinformatics

    2 publications · 439 citations

    2

    h-index

  2. Proceedings of the VLDB Endowment

    PVLDB · 2 publications · 149 citations

    2

    h-index

  3. Computers & Graphics

    1 publications · 29 citations

    1

    h-index

  4. Proceedings

    IV · 1 publications · 21 citations

    1

    h-index

  5. Future Generation Computer Systems

    FGCS · 1 publications · 30 citations

    1

    h-index

1–5