Fig. 10.

Overview of our methodological approach for building the multiplex temporal network $G$. Data from the overlapping time windows $t_i$ yield the weighted undirected user similarity networks $G_i$ that constitute the layers of $G$. Then, dynamic community detection is performed on the multiplex temporal network $G$.