Machine learningNetwork science

Weighted Temporal Network Analysis

Weighted temporal network analysis studies networks whose edges carry numerical weights — representing interaction strength, frequency, or intensity — and whose structure changes over time. It combines the time-varying perspective of temporal network analysis with the quantitative precision of weighted graph metrics, revealing not only when connections exist but how strong they are at each moment.

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Sources

  1. Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125. DOI: 10.1016/j.physrep.2012.04.004
  2. Barrat, A., Barthelemy, M., Pastor-Satorras, R. & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI: 10.1073/pnas.0400087101

Related methods

ScholarGateWeighted Temporal Network Analysis (Weighted Temporal Network Analysis (Time-Varying Weighted Graph Analysis)). Retrieved 2026-06-04 from https://scholargate.app/en/network-analysis/weighted-temporal-network-analysis