Facetsviewer: A Tool For Multi-Faceted Decomposition Of Complex Networks

The availability of large-scale network data has given rise to the opportunity to investigate higher level organization of these networks using graph theoretic analysis. In this paper, we demonstrate a novel network decomposition tool called FacetsViewer in order to make sense of the deluge of network data. In contrast to traditional graph clustering techniques, it finds not just a single decomposition of the network, but a multi-faceted atlas of semantically meaningful decompositions that portray alternative perspectives of the landscape of the underlying network. Each facet in the atlas represents a distinct interpretation of how the network can be meaningfully decomposed and organized. To this end, FacetsViewer maximizes interpretative value of the atlas by optimizing inter-facet semantic and structural orthogonality. Specifically, we demonstrate various features of FacetsViewer and its superior ability to generate and visualize multi-faceted atlas of complex networks.