قارن الطرق

	تحليل الشبكات الاجتماعية الزمنية	تحليل الانتشار الشبكي
المجال	تحليل الشبكات	تحليل الشبكات
العائلة	Machine learning	Machine learning
سنة النشأة	2000s–2010s	1927 (epidemic roots); network formalization 1990s–2000s
صاحب الطريقة	Moody, J.; Holme, P.; Saramäki, J.	Kermack, W. O. & McKendrick, A. G.
النوع	Longitudinal network analysis	Simulation / analytical model
المصدر التأسيسي	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.
الأسماء البديلة	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA	diffusion on networks, information diffusion, contagion spreading model, network propagation model
ذات صلة	4	5
الملخص	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.