Comparer des méthodes

	Analyse de la diffusion sur réseaux temporels	Analyse des réseaux sociaux temporels
Domaine	Analyse de réseaux	Analyse de réseaux
Famille	Machine learning	Machine learning
Année d'origine	2012	2000s–2010s
Auteur d'origine	Holme, P. & Saramäki, J.	Moody, J.; Holme, P.; Saramäki, J.
Type	Network analysis framework	Longitudinal network analysis
Source fondatrice	Holme, P. & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
Alias	TNDA, dynamic network diffusion, time-varying network spreading, diffusion on temporal networks	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
Apparentées	5	4
Résumé	Temporal Network Diffusion Analysis studies how information, disease, influence, or other contagions spread through networks whose structure changes over time. By modeling edges as time-stamped contacts rather than static links, it captures the critical role of timing and ordering in determining which nodes get reached, how fast, and through which pathways — producing conclusions that static network models systematically miss.	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.