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| Analisis Jaringan Sosial Berbobot× | Analisis Rangkaian Sosial× | |
|---|---|---|
| Bidang | Analisis Rangkaian | Analisis Rangkaian |
| Keluarga | Machine learning | Machine learning |
| Tahun asal≠ | 2004–2010 | 1934 (sociometry); 1994 (modern formalization) |
| Pengasas≠ | Barrat, A.; Opsahl, T. et al. | Moreno, J.L.; formalized by Wasserman & Faust |
| Jenis≠ | Network analysis framework | Structural/relational analysis framework |
| Sumber perintis≠ | 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 |
| Alias | Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis | SNA, network analysis, sociometric analysis, relational analysis |
| Berkaitan≠ | 6 | 5 |
| Ringkasan≠ | 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. |
| ScholarGateSet data ↗ |
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