Methoden vergelijken

	Gerichte Multiplexnetwerkanalyse	Multilayer Network Diffusion Analysis
Vakgebied	Netwerkanalyse	Netwerkanalyse
Familie	Machine learning	Machine learning
Jaar van ontstaan	2013–2014	2013–2014
Grondlegger	Kivela, M.; De Domenico, M. et al.	Gomez, S. et al.; Boccaletti, S. et al.
Type	Multi-layer directed graph framework	Network diffusion model
Oorspronkelijke bron	Kivela, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2(3), 203–271.	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.
Aliassen	directed multilayer network analysis, directed multiplex graphs, asymmetric multiplex network analysis, DMNA	multiplex diffusion analysis, multilayer spreading analysis, cross-layer contagion analysis, diffusion on multiplex networks
Verwant	6	6
Samenvatting	Directed multiplex network analysis models systems where the same set of nodes are connected by multiple types of directed (asymmetric) relationships across distinct layers — such as citation flows, information cascades, or authority hierarchies co-existing simultaneously. It extends multiplex network analysis by preserving both layer identity and edge directionality, enabling richer structural and dynamic insights.	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.