Spectral Centrality

Spectral Centrality is a network centrality measure that identifies the importance of nodes based on the principal eigenvector of the network's adjacency matrix, thereby capturing influence through the global structure of the network.

10

Publications

528

Citations

25

Authors

17

Institutions

Publications per year

2017–2026

3

Variants

Eigenvector Centrality

Authors

25

  1. GZ
    Guyu Zhao

    Yanshan University, China

    1 publications · 14 citations

    1

    h-index

  2. DJ
    Desmond J. Higham

    University of Strathclyde, United Kingdom

    1 publications · 81 citations

    1

    h-index

  3. FT
    Francesco Tudisco

    Gran Sasso Science Institute, Italy

    1 publications · 81 citations

    1

    h-index

  4. VN
    Vincenzo Nicosia

    Queen Mary University of London, United Kingdom

    1 publications · 78 citations

    1

    h-index

  5. SF
    Santo Fortunato

    Institute for Scientific Interchange, Italy

    1 publications · 155 citations

    1

    h-index

1–5 of 25

Venues

  1. Physical Review E

    PRE · 2 publications · 174 citations

    2

    h-index

  2. Scientific Reports

    1 publications · 78 citations

    1

    h-index

  3. Journal of Mathematical Sociology

    1 publications · 37 citations

    1

    h-index

  4. PLoS Computational Biology

    1 publications · 42 citations

    1

    h-index

  5. Edinburgh Research Explorer

    Repository · 1 publications · 81 citations

    1

    h-index

1–5