قارن الطرق

	تحليل الشبكات الزمنية الموزونة	تحليل الشبكات الاجتماعية الموزونة
المجال	تحليل الشبكات	تحليل الشبكات
العائلة	Machine learning	Machine learning
سنة النشأة	2004–2012	2004–2010
صاحب الطريقة	Holme, P. & Saramaki, J. (temporal networks); Barrat et al. (weighted networks)	Barrat, A.; Opsahl, T. et al.
النوع	Network analysis technique	Network analysis framework
المصدر التأسيسي	Holme, P. & Saramaki, J. (2012). Temporal networks. Physics Reports, 519(3), 97–125.	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.
الأسماء البديلة	WTNA, weighted time-varying network analysis, weighted dynamic network analysis, weighted evolving network analysis	Weighted SNA, valued network analysis, tie-strength network analysis, weighted graph analysis
ذات صلة	6	6
الملخص	Weighted temporal network analysis studies networks whose edges carry numerical weights — representing interaction strength, frequency, or intensity — and whose structure changes over time. It combines the time-varying perspective of temporal network analysis with the quantitative precision of weighted graph metrics, revealing not only when connections exist but how strong they are at each moment.	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.