手法を比較

	時間的社会ネットワーク分析	時間的コミュニティ検出
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	2000s–2010s	2010
提唱者	Moody, J.; Holme, P.; Saramäki, J.	Mucha, P. J. et al.
種類	Longitudinal network analysis	Network clustering algorithm
原典	Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876–878.
別名	TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA	dynamic community detection, time-varying community detection, evolutionary community detection, longitudinal community detection
関連	4	6
概要	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.	Temporal community detection identifies cohesive groups (communities) in networks whose structure changes over time. By treating each time snapshot as a network layer and coupling consecutive layers, it reveals how communities form, merge, split, grow, or dissolve — turning a sequence of static snapshots into a continuous narrative of group evolution.