Random-walk Centrality

Random-Walk Centrality is a network centrality metric that quantifies the importance of a node based on the frequency with which it is visited during a random walk process on a graph, distinguishing it from other centrality measures by its reliance on dynamic traversal probabilities rather than static topological features.

24

Publications

1.5K

Citations

66

Authors

46

Institutions

Publications per year

2017–2026

12

Authors

66

  1. FJ
    Fabian J. Theis

    Helmholtz Zentrum München, Germany

    2 publications · 221 citations

    2

    h-index

  2. MC
    Manuel Curado

    University of Alicante, Spain

    2 publications · 95 citations

    2

    h-index

  3. LT
    Leandro Tortosa

    University of Alicante, Spain

    2 publications · 95 citations

    2

    h-index

  4. EO
    Eric O'n. Fisher

    The Ohio State University, United States

    2 publications · 221 citations

    2

    h-index

  5. JF
    José F. Vicent

    University of Alicante, Spain

    2 publications · 95 citations

    2

    h-index

1–5 of 66

Venues

  1. Information Sciences

    2 publications · 170 citations

    2

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  2. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 1 publications · 77 citations

    1

    h-index

  3. SIAM Journal on Applied Mathematics

    1 publications · 17 citations

    1

    h-index

  4. Physical Review E

    PRE · 1 publications · 157 citations

    1

    h-index

  5. 1

    h-index

1–5