Comparer des méthodes

	Analyse de la diffusion sur réseaux multicouches	Analyse de la diffusion sur réseaux temporels
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	2013–2014	2012
Auteur d'origine	Gomez, S. et al.; Boccaletti, S. et al.	Holme, P. & Saramäki, J.
Type	Network diffusion model	Network analysis framework
Source fondatrice	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.	Holme, P. & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
Alias	multiplex diffusion analysis, multilayer spreading analysis, cross-layer contagion analysis, diffusion on multiplex networks	TNDA, dynamic network diffusion, time-varying network spreading, diffusion on temporal networks
Apparentées	6	5
Résumé	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.	Temporal Network Diffusion Analysis studies how information, disease, influence, or other contagions spread through networks whose structure changes over time. By modeling edges as time-stamped contacts rather than static links, it captures the critical role of timing and ordering in determining which nodes get reached, how fast, and through which pathways — producing conclusions that static network models systematically miss.