Linganisha mbinu

	Uchanganuzi wa Uenezaji wa Mitandao yenye Uzito	Uchanganuzi wa Uenezaji wa Mtandao
Nyanja	Uchanganuzi wa Mitandao	Uchanganuzi wa Mitandao
Familia	Machine learning	Machine learning
Mwaka wa asili	2004	1927 (epidemic roots); network formalization 1990s–2000s
Mwanzilishi	Barrat, A.; Newman, M. E. J.	Kermack, W. O. & McKendrick, A. G.
Aina	Network diffusion model	Simulation / analytical model
Chanzo asilia	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.
Majina mbadala	WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion	diffusion on networks, information diffusion, contagion spreading model, network propagation model
Zinazohusiana	6	5
Muhtasari	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.