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| Phân tích mạng xã hội 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≠ | 2000s–2010s | 1934 (sociometry); 1994 (modern formalization) |
| Người khởi xướng≠ | Moody, J.; Holme, P.; Saramäki, J. | Moreno, J.L.; formalized by Wasserman & Faust |
| Loại≠ | Longitudinal network analysis | Structural/relational analysis framework |
| Công trình gốc≠ | Holme, P., & Saramäki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Tên gọi khác | TSNA, longitudinal social network analysis, time-varying network analysis, dynamic SNA | SNA, network analysis, sociometric analysis, relational analysis |
| Liên quan≠ | 4 | 5 |
| Tóm tắt≠ | 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. | 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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