Comparar métodos

	Análise de Difusão em Redes Ponderadas	Análise de Difusão em Redes
Área	Análise de redes	Análise de redes
Família	Machine learning	Machine learning
Ano de origem	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
Fonte 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.
Outros nomes	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
Resumo	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.