Usporedite metode

	Vremenska svojstvena centralnost	Vremenska analiza društvenih mreža
Područje	Analiza mreža	Analiza mreža
Obitelj	Machine learning	Machine learning
Godina nastanka	2011-2017	2000s–2010s
Tvorac	Grindrod, P.; Higham, D. J.; Taylor, D. et al.	Moody, J.; Holme, P.; Saramäki, J.
Vrsta	Centrality measure for temporal networks	Longitudinal network analysis
Temeljni izvor	Grindrod, P., Parsons, M. C., Higham, D. J., & Estrada, E. (2011). Communicability across evolving networks. Physical Review E, 83(4), 046120.	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
Drugi nazivi	dynamic eigenvector centrality, time-varying eigenvector centrality, TEC, temporal communicability centrality	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
Srodne	5	4
Sažetak	Temporal eigenvector centrality extends the classical eigenvector centrality to networks that change over time. By accounting for the ordering and timing of connections, it identifies nodes that are influential not merely because of many simultaneous connections, but because they sit at the crossroads of sequentially important pathways across multiple time slices of the network.	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.