Dynamic Community Detection Using Nonnegative Matrix Factorization

This paper presents a dynamic community detection method based on nonnegative matrix factorization (NMF). The approach effectively identifies communities in evolving networks by leveraging the advantages of NMF, which ensures the interpretability and scalability of the detection process. The method is particularly suitable for large-scale temporal networks where community structures evolve over time.