Methoden vergelijken

	Multilayer Network Diffusion Analysis	Netwerkdiffusieanalyse
Vakgebied	Netwerkanalyse	Netwerkanalyse
Familie	Machine learning	Machine learning
Jaar van ontstaan	2013–2014	1927 (epidemic roots); network formalization 1990s–2000s
Grondlegger	Gomez, S. et al.; Boccaletti, S. et al.	Kermack, W. O. & McKendrick, A. G.
Type	Network diffusion model	Simulation / analytical model
Oorspronkelijke bron	Gomez, S., Diaz-Guilera, A., Gomez-Gardenes, J., Perez-Vicente, C. J., Moreno, Y., & Arenas, A. (2013). Diffusion dynamics on multiplex networks. Physical Review Letters, 110(2), 028701.	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.
Aliassen	multiplex diffusion analysis, multilayer spreading analysis, cross-layer contagion analysis, diffusion on multiplex networks	diffusion on networks, information diffusion, contagion spreading model, network propagation model
Verwant	6	5
Samenvatting	Multilayer Network Diffusion Analysis models how information, disease, or influence spreads across a system composed of multiple, interconnected network layers. By coupling diffusion processes across layers — for instance social ties, transport routes, and online channels simultaneously — it reveals how cross-layer interactions accelerate or dampen spreading and lowers epidemic thresholds compared to single-layer models.	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.