Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Динамический анализ эго-сетей× | Социальный сетевой анализ× | |
|---|---|---|
| Область | Сетевой анализ | Сетевой анализ |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 1990s–2015 | 1934 (sociometry); 1994 (modern formalization) |
| Автор метода≠ | Burt, R. S.; Wellman, B. (foundational ego-net); dynamic extension developed across the 1990s–2010s | Moreno, J.L.; formalized by Wasserman & Faust |
| Тип≠ | Longitudinal network analysis framework | Structural/relational analysis framework |
| Основополагающий источник≠ | Burt, R. S. (1992). Structural Holes: The Social Structure of Competition. Harvard University Press. ISBN: 978-0-674-84372-1 | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Другие названия | longitudinal ego network analysis, temporal ego network analysis, personal network dynamics, dynamic personal network analysis | SNA, network analysis, sociometric analysis, relational analysis |
| Связанные≠ | 3 | 5 |
| Сводка≠ | Dynamic ego network analysis examines how the personal network surrounding a focal individual (the ego) changes over time. By collecting the same ego-centered network data at multiple time points, researchers can track tie formation and dissolution, shifts in network composition, and changes in structural properties such as density, constraint, and network size — and link these dynamics to individual outcomes. | 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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