Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Социальный сетевой анализ× | Triad Census× | |
|---|---|---|
| Область≠ | Сетевой анализ | Sociology |
| Семейство≠ | Machine learning | Process / pipeline |
| Год появления≠ | 1934 (sociometry); 1994 (modern formalization) | 1970 |
| Автор метода≠ | Moreno, J.L.; formalized by Wasserman & Faust | Paul Holland & Samuel Leinhardt |
| Тип≠ | Structural/relational analysis framework | Enumeration of the 16 isomorphism classes of directed triads |
| Основополагающий источник≠ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 | Holland, P. W., & Leinhardt, S. (1970). A method for detecting structure in sociometric data. American Journal of Sociology, 76(3), 492–513. DOI ↗ |
| Другие названия | SNA, network analysis, sociometric analysis, relational analysis | triad count, triadic census, 16-type triad census, MAN triad census |
| Связанные≠ | 5 | 4 |
| Сводка≠ | 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. | The triad census counts how many of a directed network's three-actor subgroups fall into each of the 16 possible types of triad, providing a compact fingerprint of the network's local structure. Introduced by Paul Holland and Samuel Leinhardt in 1970, it is the standard way to test structural theories — balance, clustering, transitivity, ranked clusters — by comparing the observed distribution of triad types against what a random network would produce. |
| ScholarGateНабор данных ↗ |
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