Uporedite metode

	Analiza višeslojnih vremenskih mreža	Analiza vremenskih mreža
Oblast	Analiza mreža	Analiza mreža
Porodica	Machine learning	Process / pipeline
Godina nastanka	2012–2014	2012
Tvorac	Kivela, M. et al.; Holme, P. & Saramaki, J.	Holme & Saramäki (2012) — seminal framework
Tip	Network analysis framework	Dynamic graph analysis
Temeljni izvor	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.	Holme, P. & Saramäki, J. (2012). Temporal Networks. Physics Reports, 519(3), 97-125.
Drugi nazivi	MTNA, temporal multilayer network analysis, time-varying multilayer network analysis, dynamic multilayer network analysis	dynamic network analysis, time-varying network analysis, Zamansal Ağ Analizi (Temporal / Dynamic Networks)
Srodne	4	3
Sažetak	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.	Temporal network analysis, formalised by Holme and Saramäki in their landmark 2012 Physics Reports survey, is the study of networks in which edges appear and disappear over time. Rather than collapsing all contacts into a single static graph, the approach preserves the precise timing of interactions — whether as contact sequences, time-stamped event lists, or windowed snapshots — and uses that timing to track how influence, disease, or information can actually propagate through the system.