Machine learningNetwork science
Weighted Social Network Analysis
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.
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Sources
- 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: 10.1073/pnas.0400087101 ↗
- Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251. DOI: 10.1016/j.socnet.2010.03.006 ↗
Related methods
Referenced by
Weighted Betweenness CentralityWeighted Closeness CentralityWeighted Community DetectionWeighted Ego Network AnalysisWeighted Exponential Random Graph ModelWeighted Modularity AnalysisWeighted Network Diffusion AnalysisWeighted Stochastic Block ModelWeighted Temporal Network AnalysisWeighted Two-Mode Network Analysis