Comparer des méthodes

	Analyse de la diffusion sur réseaux pondérés	PageRank pondéré
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	2004	2004
Auteur d'origine	Barrat, A.; Newman, M. E. J.	Xing, W. & Ghorbani, A.
Type	Network diffusion model	Centrality measure / ranking algorithm
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.	Xing, W., & Ghorbani, A. (2004). Weighted PageRank algorithm. Proceedings of the Second Annual Conference on Communication Networks and Services Research (CNSR '04), pp. 305–314. IEEE.
Alias	WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion	WPR, weighted page rank, edge-weighted PageRank, strength-based PageRank
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.	Weighted PageRank extends the classic PageRank algorithm to networks where edges carry different strengths or frequencies, distributing importance proportionally to both incoming and outgoing edge weights rather than treating all links equally. This makes it substantially more informative than binary PageRank in any network where connection strength matters.