Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Krackhardt Hierarchy Measures× | Социальный сетевой анализ× | |
|---|---|---|
| Область≠ | Sociology | Сетевой анализ |
| Семейство≠ | Process / pipeline | Machine learning |
| Год появления≠ | 1994 | 1934 (sociometry); 1994 (modern formalization) |
| Автор метода≠ | David Krackhardt | Moreno, J.L.; formalized by Wasserman & Faust |
| Тип≠ | Set of four graph-theoretic indices of how hierarchical a network is | Structural/relational analysis framework |
| Основополагающий источник≠ | Krackhardt, D. (1994). Graph theoretical dimensions of informal organizations. In K. M. Carley & M. J. Prietula (Eds.), Computational Organization Theory (pp. 89–111). Lawrence Erlbaum Associates. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Другие названия | Krackhardt GTD, graph-theoretic dimensions of hierarchy, Krackhardt connectedness-hierarchy-efficiency-LUB, out-tree hierarchy measures | SNA, network analysis, sociometric analysis, relational analysis |
| Связанные | 5 | 5 |
| Сводка≠ | Krackhardt's graph-theoretic dimensions provide four indices that together measure how closely a directed network approximates a pure hierarchy — formally, an out-tree. The dimensions are connectedness (is everyone linked?), hierarchy (are ties asymmetric, i.e., non-reciprocated?), efficiency (are there no redundant ties?), and least upper bound (does every pair share a common superior?). Each is scaled from 0 to 1, and a network scoring 1 on all four is a perfect hierarchy. | 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. |
| ScholarGateНабор данных ↗ |
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