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Detecting the Community Structure and Activity Patterns of Temporal Networks: A Non-Negative Tensor Factorization Approach

Figure 4

NTF decomposition of an empirical temporal network.

Left panel: core consistency curve. For each value of the number of components used for factorization, the core consistency values for the 5 best decompositions are reported (crosses). The solid line is a guide for the eye. A crossover between two regimes is visible for . Right panel: component-node matrix for components. Rows correspond to network nodes and columns to components. The matrix is obtained from the factor by classifying each node as belonging (lighter rectangles) or not belonging (dark blue rectangles) to a given component. The order of the nodes has been rearranged to expose the block structure of the matrix. Colors identify components, and the community structures that can be matched to school classes are annotated with the corresponding class name.

doi: https://doi.org/10.1371/journal.pone.0086028.g004