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| Irányított multiplex hálózatelemzés× | Többrétegű Hálózati Diffúzió Elemzés× | |
|---|---|---|
| Tudományterület | Hálózatelemzés | Hálózatelemzés |
| Módszercsalád | Machine learning | Machine learning |
| Keletkezés éve | 2013–2014 | 2013–2014 |
| Megalkotó≠ | Kivela, M.; De Domenico, M. et al. | Gomez, S. et al.; Boccaletti, S. et al. |
| Típus≠ | Multi-layer directed graph framework | Network diffusion model |
| Alapmű≠ | 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. DOI ↗ | 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. DOI ↗ |
| Alternatív nevek | 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 |
| Kapcsolódó | 6 | 6 |
| Összefoglaló≠ | 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. |
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