Block-Organized Topology Visualization for Visual Exploration of Signed Networks

Many networks nowadays contain both positive and negative relationships, such as ratings and conflicts, which are often mixed in the layouts of network visualization represented by the layouts of node-link diagram and node indices of matrix representation. In this work, we present a visual analysis framework for visualizing signed networks through emphasizing different effects of signed edges on network topologies. The theoretical foundation of the visual analysis framework comes from the spectral analysis of data patterns in the high-dimensional spectral space. Based on the spectral analysis results, we present a block-organized visualization approach in the hybrid form of matrix, node-link, and arc diagrams with the focus on revealing topological structures of signed networks. We demonstrate with a detailed case study that block-organized visualization and spectral space exploration can be combined to analyze topologies of signed networks effectively.