Comparer des méthodes

	Centralité d'intermédiarité temporelle	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	Kim, H. & Anderson, R.; Holme, P. & Saramäki, J.	Moody, J.; Holme, P.; Saramäki, J.
Type	Centrality measure for temporal networks	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	TBC, time-varying betweenness centrality, dynamic betweenness centrality, time-respecting betweenness	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
Apparentées	6	4
Résumé	Temporal Betweenness Centrality (TBC) extends classical betweenness centrality to time-stamped networks by counting how often a node lies on time-respecting shortest paths — paths that traverse edges in chronological order. It identifies nodes that act as temporal brokers, controlling information or resource flow as it evolves over time, rather than in a static snapshot.	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.