Comparer des méthodes

	Analyse de la diffusion sur réseaux pondérés	Analyse de réseaux multiplex
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	2004	2014
Auteur d'origine	Barrat, A.; Newman, M. E. J.	Kivela, M.; Boccaletti, S. et al.
Type	Network diffusion model	Structural network 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.	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.
Alias	WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion	multiplex networks, multi-layer network analysis, multilayer network analysis, MNA
Apparentées	6	6
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.	Multiplex network analysis studies systems where the same set of nodes is connected by multiple distinct types of relationships, each represented as a separate network layer. By analyzing layers simultaneously rather than in isolation, it reveals how different relation types interact, reinforce each other, or compensate for one another across the same actors or entities.