So sánh phương pháp

	Phân tích Tính Mô-đun Theo Thời gian	Phát hiện cộng đồng động
Lĩnh vực	Phân tích mạng lưới	Phân tích mạng lưới
Họ	Machine learning	Machine learning
Năm ra đời	2010	2010 (key formalization); earlier work 2002–2009
Người khởi xướng	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P.	Mucha, P. J. et al. (key formalization); earlier work by Girvan & Newman (2002)
Loại	Community detection (temporal extension of modularity optimization)	Graph clustering / community discovery
Công trình gốc	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.	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.
Tên gọi khác	dynamic modularity, time-varying modularity, longitudinal community detection, temporal community structure analysis	DCD, temporal community detection, evolving community detection, dynamic graph clustering
Liên quan	5	5
Tóm tắt	Temporal modularity analysis extends standard modularity-based community detection to time-varying networks by treating each time slice as a network layer and coupling adjacent layers with inter-temporal links. This allows researchers to identify how communities form, persist, merge, split, and dissolve over time in dynamic relational data.	Dynamic community detection identifies groups of densely connected nodes in networks that evolve over time, tracking how communities form, merge, split, and dissolve across temporal snapshots. Developed to extend static modularity optimization to time-varying structures, it is widely used in social, biological, and communication network research.