Comparer des méthodes

	Analyse de la diffusion sur réseaux pondérés	Analyse de la diffusion en réseau
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	2004	1927 (epidemic roots); network formalization 1990s–2000s
Auteur d'origine	Barrat, A.; Newman, M. E. J.	Kermack, W. O. & McKendrick, A. G.
Type	Network diffusion model	Simulation / analytical model
Source fondatrice	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.	Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721.
Alias	WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion	diffusion on networks, information diffusion, contagion spreading model, network propagation model
Apparentées	6	5
Résumé	Weighted Network Diffusion Analysis models how information, influence, disease, or resources spread through a network whose edges carry quantitative strength values. By letting tie weights govern transition probabilities, the method produces more realistic spreading dynamics than binary-edge diffusion, revealing which high-traffic pathways dominate propagation in social, biological, and information networks.	Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally.