Salīdzināt metodes

	Diverģētās multiplikācijas tīklu analīze	Daudzslāņu sociālo tīklu analīze
Nozare	Tīklu analīze	Tīklu analīze
Saime	Machine learning	Machine learning
Izcelsmes gads	2013–2014	2014
Autors	Kivela, M.; De Domenico, M. et al.	Kivela, M.; Boccaletti, S. et al.
Tips	Multi-layer directed graph framework	Structural network analysis framework
Pirmavots	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.	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.
Citi nosaukumi	directed multilayer network analysis, directed multiplex graphs, asymmetric multiplex network analysis, DMNA	MSNA, multiplex network analysis, multilayer network analysis, interconnected network analysis
Saistītās	6	6
Kopsavilkums	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 social network analysis extends classical single-layer network methods to settings where actors are connected through multiple, distinct types of ties — such as friendship, professional collaboration, and online interaction — simultaneously. By modeling each type of relationship as a separate layer and explicitly representing connections across layers, it captures structural complexity that a single aggregated network would hide.