手法を比較

	時間的次数中心性	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	2011–2012	2000s–2010s
提唱者	Holme, P.; Saramaki, J.; Kim, H.; Anderson, R.	Moody, J.; Holme, P.; Saramäki, J.
種類	Centrality measure (temporal extension)	Longitudinal network analysis
原典	Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.
別名	time-varying degree centrality, dynamic degree centrality, temporal node degree, TDC	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA
関連	6	4
概要	Temporal degree centrality extends the classic degree centrality to time-varying networks by counting how many distinct contacts a node accumulates over time. Rather than collapsing a dynamic network into a single static graph, it preserves the temporal order of edges, yielding a more faithful measure of a node's activity and reachability across the observation window.	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.