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| Multilayer Temporal Network Analysis× | Multiplex-Netzwerkanalyse× | |
|---|---|---|
| Fachgebiet | Netzwerkanalyse | Netzwerkanalyse |
| Familie | Machine learning | Machine learning |
| Entstehungsjahr≠ | 2012–2014 | 2014 |
| Urheber≠ | Kivela, M. et al.; Holme, P. & Saramaki, J. | Kivela, M.; Boccaletti, S. et al. |
| Typ≠ | Network analysis framework | Structural network model |
| Wegweisende Quelle | 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 ↗ | 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 ↗ |
| Aliasnamen | MTNA, temporal multilayer network analysis, time-varying multilayer network analysis, dynamic multilayer network analysis | multiplex networks, multi-layer network analysis, multilayer network analysis, MNA |
| Verwandt≠ | 4 | 6 |
| Zusammenfassung≠ | Multilayer temporal network analysis studies relational systems in which nodes interact through multiple distinct types of ties that all evolve over time. By modeling each relationship type as a separate layer and tracking how those layers change across time snapshots, the method reveals how cross-layer dynamics and temporal patterns jointly shape information flow, influence spread, and community structure. | Multiplex network analysis studies systems where the same set of nodes is connected by multiple distinct types of relationships, each represented as a separate network layer. By analyzing layers simultaneously rather than in isolation, it reveals how different relation types interact, reinforce each other, or compensate for one another across the same actors or entities. |
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