Name
Abstract | ||
|---|---|---|
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 fromthe spectral analysis of data patterns in the high-dimensional spectral space. Based on the spectral analysis results, we present a block-organizedvisualization approach in the hybrid form of matrix, node-link, and arcdiagrams with the focus on revealing topological structuresof 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. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/ICDMW.2015.117 | ICDM Workshops |
Keywords | Field | DocType |
Hybrid network visualization, block-organized visualization, signed networks, spectral analysis, visual analytics | Graph drawing,Data mining,Computer science,Visual analytics,Diagram,Theoretical computer science,Spectral space,Artificial intelligence,Topology,Data visualization,Visualization,Network topology,Matrix representation,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.35 | 23 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xianlin Hu | 1 | 19 | 2.06 |
| Leting Wu | 2 | 95 | 5.68 |
| Aidong Lu | 3 | 353 | 30.18 |
| Xintao Wu | 4 | 892 | 76.91 |