Temporal Network Sampling

Temporal Network Sampling is a methodological framework within dynamic network analysis that systematically selects time-indexed subgraphs or interaction instances from a temporal network to preserve evolving structural and temporal properties for scalable and representative analysis.

9

Publications

345

Citations

24

Authors

12

Institutions

Publications per year

2017–2026

3

Authors

24

  1. BL
    Bin Li

    Yangzhou University, China

    1 publications · 56 citations

    1

    h-index

  2. NM
    Naoki Masuda

    The University of Tokyo, Japan

    1 publications · 39 citations

    1

    h-index

  3. RR
    Ryan R. James

    Battelle, United States

    1 publications · 40 citations

    1

    h-index

  4. SK
    Steven K. Thompson

    Pennsylvania State University, United States

    1 publications · 12 citations

    1

    h-index

  5. NM
    Nahla Mohamed Ahmed

    Yangzhou University, China

    1 publications · 56 citations

    1

    h-index

1–5 of 24

Venues

  1. SIAM Review

    1 publications · 84 citations

    1

    h-index

  2. Environmental Science & Technology

    1 publications · 40 citations

    1

    h-index

  3. Physical review. E

    PRE · 1 publications · 39 citations

    1

    h-index

  4. Earth system science data

    1 publications · 30 citations

    1

    h-index

  5. Proceedings of the ACM Web Conference 2022

    Conference · 1 publications · 17 citations

    1

    h-index

1–5