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Analyse des réseaux temporels pondérés×Analyse des réseaux sociaux pondérés×
DomaineAnalyse de réseauxAnalyse de réseaux
FamilleMachine learningMachine learning
Année d'origine2004–20122004–2010
Auteur d'origineHolme, P. & Saramaki, J. (temporal networks); Barrat et al. (weighted networks)Barrat, A.; Opsahl, T. et al.
TypeNetwork analysis techniqueNetwork analysis framework
Source fondatriceHolme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125. DOI ↗Barrat, A., Barthélemy, 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 ↗
AliasWTNA, weighted time-varying network analysis, weighted dynamic network analysis, weighted evolving network analysisWeighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
Apparentées66
RésuméWeighted 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.Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships.
ScholarGateJeu de données
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  1. v1
  2. 2 Sources
  3. PUBLISHED

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ScholarGateComparer des méthodes: Weighted Temporal Network Analysis · Weighted Social Network Analysis. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare