Bandingkan metode

	Analisis Difusi Jaringan Berbobot	Analisis Jaringan Sosial Berbobot
Bidang	Analisis Jaringan	Analisis Jaringan
Keluarga	Machine learning	Machine learning
Tahun asal	2004	2004–2010
Pencetus	Barrat, A.; Newman, M. E. J.	Barrat, A.; Opsahl, T. et al.
Tipe	Network diffusion model	Network analysis framework
Sumber perintis	Barrat, A., Barthelemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. Proceedings of the National Academy of Sciences, 101(11), 3747–3752.	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.
Alias	WNDA, weighted diffusion process, edge-weighted spreading analysis, weighted information diffusion	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
Terkait	6	6
Ringkasan	Weighted Network Diffusion Analysis models how information, influence, disease, or resources spread through a network whose edges carry quantitative strength values. By letting tie weights govern transition probabilities, the method produces more realistic spreading dynamics than binary-edge diffusion, revealing which high-traffic pathways dominate propagation in social, biological, and information networks.	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.