Comparar métodos

	Análisis de Difusión en Redes Ponderadas	Análisis de Difusión en Red
Campo	Análisis de redes	Análisis de redes
Familia	Machine learning	Machine learning
Año de origen	2004	1927 (epidemic roots); network formalization 1990s–2000s
Autor original	Barrat, A.; Newman, M. E. J.	Kermack, W. O. & McKendrick, A. G.
Tipo	Network diffusion model	Simulation / analytical model
Fuente seminal	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
Relacionados	6	5
Resumen	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.