Virality Detection

Virality Detection is a computational method designed to identify content that exhibits rapid and widespread dissemination across social networks by analyzing engagement dynamics and propagation patterns distinct from ordinary information diffusion.

116

Publications

10.3K

Citations

327

Authors

182

Institutions

Publications per year

2017–2026

59

Authors

327

  1. LX
    Lexing Xie

    Australian National University, Australia

    5 publications · 239 citations

    5

    h-index

  2. MG
    Marco Guerini

    Fondazione Bruno Kessler, Italy

    4 publications · 118 citations

    4

    h-index

  3. MR
    Marian-Andrei Rizoiu

    Australian National University, Australia

    4 publications · 158 citations

    4

    h-index

  4. KH
    Kwan Hui Lim

    The University of Melbourne, Australia

    3 publications · 67 citations

    3

    h-index

  5. PS
    Paulo Shakarian

    Arizona State University, United States

    3 publications · 48 citations

    3

    h-index

1–5 of 327

Venues

  1. 9

    h-index

  2. Expert Systems with Applications

    3 publications · 147 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 42 citations

    3

    h-index

  4. SSRN Electronic Journal

    Repository · 2 publications · 31 citations

    2

    h-index

  5. 2

    h-index

1–5