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	Multilayer Temporal Network Analysis	時間的ネットワーク分析
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Process / pipeline
提唱年	2012–2014	2012
提唱者	Kivela, M. et al.; Holme, P. & Saramaki, J.	Holme & Saramäki (2012) — seminal framework
種類	Network analysis framework	Dynamic graph analysis
原典	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.
別名	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)
関連	4	3
概要	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.