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| Phát hiện cộng đồng theo thời gian× | Phân tích mạng xã hội× | |
|---|---|---|
| Lĩnh vực | Phân tích mạng lưới | Phân tích mạng lưới |
| Họ | Machine learning | Machine learning |
| Năm ra đời≠ | 2010 | 1934 (sociometry); 1994 (modern formalization) |
| Người khởi xướng≠ | Mucha, P. J. et al. | Moreno, J.L.; formalized by Wasserman & Faust |
| Loại≠ | Network clustering algorithm | Structural/relational analysis framework |
| 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. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Tên gọi khác | dynamic community detection, time-varying community detection, evolutionary community detection, longitudinal community detection | SNA, network analysis, sociometric analysis, relational analysis |
| Liên quan≠ | 6 | 5 |
| Tóm tắt≠ | 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. | Social Network Analysis (SNA) is a structural method that maps and measures relationships and flows between people, groups, organizations, or other entities modeled as nodes connected by ties (edges). Rather than focusing on individual attributes, SNA reveals how the pattern of connections shapes behavior, influence, information flow, and outcomes within a system. |
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