قارن الطرق

	تحليل النمطية الزماني	اكتشاف المجتمعات الزمنية
المجال	تحليل الشبكات	تحليل الشبكات
العائلة	Machine learning	Machine learning
سنة النشأة	2010	2010
صاحب الطريقة	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P.	Mucha, P. J. et al.
النوع	Community detection (temporal extension of modularity optimization)	Network clustering algorithm
المصدر التأسيسي	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876-878.	Mucha, P. J., Richardson, T., Macon, K., Porter, M. A., & Onnela, J.-P. (2010). Community structure in time-dependent, multiscale, and multiplex networks. Science, 328(5980), 876–878.
الأسماء البديلة	dynamic modularity, time-varying modularity, longitudinal community detection, temporal community structure analysis	dynamic community detection, time-varying community detection, evolutionary community detection, longitudinal community detection
ذات صلة	5	6
الملخص	Temporal modularity analysis extends standard modularity-based community detection to time-varying networks by treating each time slice as a network layer and coupling adjacent layers with inter-temporal links. This allows researchers to identify how communities form, persist, merge, split, and dissolve over time in dynamic relational data.	Temporal community detection identifies cohesive groups (communities) in networks whose structure changes over time. By treating each time snapshot as a network layer and coupling consecutive layers, it reveals how communities form, merge, split, grow, or dissolve — turning a sequence of static snapshots into a continuous narrative of group evolution.