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| Phân tích Trung tâm× | Phân tích mạng xã hội× | |
|---|---|---|
| Lĩnh vực | Phân tích mạng lưới | Phân tích mạng lưới |
| Họ≠ | Process / pipeline | Machine learning |
| Năm ra đời≠ | 1979 | 1934 (sociometry); 1994 (modern formalization) |
| Người khởi xướng≠ | Linton C. Freeman | Moreno, J.L.; formalized by Wasserman & Faust |
| Loại≠ | Descriptive / exploratory network measure family | Structural/relational analysis framework |
| Công trình gốc≠ | Freeman, L.C. (1979). Centrality in Social Networks: Conceptual Clarification. Social Networks, 1(3), 215-239. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Tên gọi khác | Merkeziyet Analizi (Degree, Betweenness, Eigenvector), node centrality, centrality measures, graph centrality | SNA, network analysis, sociometric analysis, relational analysis |
| Liên quan | 5 | 5 |
| Tóm tắt≠ | Centrality analysis is a family of network-analytic measures, formalized by Freeman (1979), that quantifies the structural importance of individual nodes within a graph. Each centrality index captures a distinct mechanism of influence: degree centrality reflects direct connectivity, betweenness centrality identifies nodes that broker information flow, closeness centrality captures proximity to all others, and eigenvector centrality (along with PageRank) rewards connection to highly connected neighbors. | 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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