Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Взвешенный анализ социальных сетей× | Социальный сетевой анализ× | |
|---|---|---|
| Область | Сетевой анализ | Сетевой анализ |
| Семейство | Machine learning | Machine learning |
| Год появления≠ | 2004–2010 | 1934 (sociometry); 1994 (modern formalization) |
| Автор метода≠ | Barrat, A.; Opsahl, T. et al. | Moreno, J.L.; formalized by Wasserman & Faust |
| Тип≠ | Network analysis framework | Structural/relational analysis framework |
| Основополагающий источник≠ | Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752. DOI ↗ | Wasserman, S. & Faust, K. (1994). Social Network Analysis: Methods and Applications. Cambridge University Press. ISBN: 978-0-521-38707-1 |
| Другие названия | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis | SNA, network analysis, sociometric analysis, relational analysis |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the existence, of their relationships. | 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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