Fig 6. The fit of each method’s partition to the ground truth partition(s).

The fit of each method’s partition (the methods are: ClueNet (its three versions: C-ST, C-D, and C-C), Louvain (L), Infomap (I), Hierarchical Infomap (HI), label propagation (LP), simulated annealing (SA), and Multistep (M)) to the ground truth (GT) partition(s), for (a) social Enron, (b) social hospital, (c) social high school, and (d) biological aging-related dynamic networks, with respect to topological (D-GDV) similarity versus interaction denseness (modularity). In the given panel, a method is good if its partition is in the same quadrant as the ground truth partition and if the two partitions both show high or low D-GDV similarity and modularity scores. In panel (a), only the three ClueNet versions match both high D-GDV similarity and low (close to 0 but positive) modularity scores of the ground truth partition. In panel (b), all three versions of ClueNet are closer to the ground truth partition than the existing methods. Note that in panel (b), the Louvain method is missing, because it did not produce any output for this network. In panel (c), all methods mimic well both high D-GDV similarity and high (positive) modularity scores, but the three ClueNet versions are the closest to the ground truth partition, along with simulated annealing and Multistep. Note that all five of these methods produce the exact same partition. So, their visualizations have been slightly manipulated by moving some of the methods’ results just a bit up/down or left/right, in order to make all five methods visible. In panel (d), there are four ground truth partitions, depending on which aging-related ground truth data is considered (BE2004, BE2008, AD, or SequenceAge; Section Data). For three of the four ground truth partitions, only the three versions of ClueNet match both high (positive) D-GDV similarity and low (close to 0 but positive) modularity scores.