手法を比較

	時間的社会ネットワーク分析	ネットワーク拡散分析
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	2000s–2010s	1927 (epidemic roots); network formalization 1990s–2000s
提唱者	Moody, J.; Holme, P.; Saramäki, J.	Kermack, W. O. & McKendrick, A. G.
種類	Longitudinal network analysis	Simulation / analytical model
原典	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Kermack, W. O. & McKendrick, A. G. (1927). A contribution to the mathematical theory of epidemics. Proceedings of the Royal Society of London A, 115(772), 700–721.
別名	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA	diffusion on networks, information diffusion, contagion spreading model, network propagation model
関連	4	5
概要	Temporal Social Network Analysis (TSNA) extends classic social network analysis by treating networks as time-varying structures. Rather than aggregating all ties into a single static snapshot, TSNA tracks when ties form, persist, and dissolve, enabling researchers to study how social structures evolve and how dynamic connectivity shapes diffusion, influence, and inequality over time.	Network diffusion analysis models how information, diseases, behaviors, or innovations spread across a graph of nodes and edges. Drawing on classical epidemic theory (SI, SIR, SIS) and modern network science, it tracks which nodes become infected, how quickly, and whether the spread reaches a global cascade or dies out locally.