手法を比較

	時間的固有ベクトル中心性	時間的社会ネットワーク分析
分野	ネットワーク分析	ネットワーク分析
系統	Machine learning	Machine learning
提唱年	2011-2017	2000s–2010s
提唱者	Grindrod, P.; Higham, D. J.; Taylor, D. et al.	Moody, J.; Holme, P.; Saramäki, J.
種類	Centrality measure for temporal networks	Longitudinal network analysis
原典	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.
別名	dynamic eigenvector centrality, time-varying eigenvector centrality, TEC, temporal communicability centrality	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
関連	5	4
概要	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.