手法を比較

	時間的固有ベクトル中心性	固有ベクトル中心性
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	1972
提唱者	Grindrod, P.; Higham, D. J.; Taylor, D. et al.	Bonacich, P.
種類	Centrality measure for temporal networks	Centrality measure
原典	Grindrod, P., Parsons, M. C., Higham, D. J., & Estrada, E. (2011). Communicability across evolving networks. Physical Review E, 83(4), 046120.	Bonacich, P. (1972). Factoring and weighting approaches to status scores and clique identification. Journal of Mathematical Sociology, 2(1), 113–120.
別名	dynamic eigenvector centrality, time-varying eigenvector centrality, TEC, temporal communicability centrality	eigenvector centrality, EC, Bonacich centrality, power centrality
関連	5	6
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.	Eigenvector centrality, introduced by Bonacich in 1972, measures a node's influence by considering not just how many neighbors it has, but how influential those neighbors are. A node scores highly if it is connected to other high-scoring nodes, making it a recursive, globally-aware measure of structural importance in a network.