Salīdzināt metodes

	Laika starpības centrālās vērtības noteikšana	Temporālā sociālo tīklu analīze
Nozare	Tīklu analīze	Tīklu analīze
Saime	Machine learning	Machine learning
Izcelsmes gads	2012	2000s–2010s
Autors	Kim, H. & Anderson, R.; Holme, P. & Saramäki, J.	Moody, J.; Holme, P.; Saramäki, J.
Tips	Centrality measure for temporal networks	Longitudinal network analysis
Pirmavots	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.
Citi nosaukumi	TBC, time-varying betweenness centrality, dynamic betweenness centrality, time-respecting betweenness	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
Saistītās	6	4
Kopsavilkums	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.