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| Generalized Blockmodeling× | 社会网络分析× | |
|---|---|---|
| 领域≠ | Sociology | 网络分析 |
| 方法族≠ | Process / pipeline | Machine learning |
| 起源年份≠ | 2005 | 1934 (sociometry); 1994 (modern formalization) |
| 提出者≠ | Patrick Doreian, Vladimir Batagelj & Anuška Ferligoj | Moreno, J.L.; formalized by Wasserman & Faust |
| 类型≠ | Direct optimization partition of a network into positions with typed blocks | Structural/relational analysis framework |
| 开创性文献≠ | Doreian, P., Batagelj, V., & Ferligoj, A. (2005). Generalized Blockmodeling. Cambridge University Press. ISBN: 978-0-521-84085-9 | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| 别名 | generalized blockmodel, direct blockmodeling, pre-specified blockmodeling, Doreian-Batagelj-Ferligoj blockmodeling | SNA, network analysis, sociometric analysis, relational analysis |
| 相关 | 5 | 5 |
| 摘要≠ | Generalized blockmodeling, developed by Doreian, Batagelj, and Ferligoj, partitions the actors of a network into positions and simultaneously characterizes the ties between positions as one of several allowed block types — null, complete, regular, dominant, and others. Rather than the indirect, two-step approach of computing equivalences and then clustering, it directly searches for the partition that minimizes the inconsistency between the observed network and an idealized block structure, optionally one the analyst pre-specifies from theory. | 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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