2022/05/16 by Jacob Miller, Stephen Kobourov, Miller, Jacob +3 · 1 citation
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Computational Physics and Python Applications #Data Visualization and Analytics #FOS: Computer and information sciences #Graphics (cs.GR) #Social and Information Networks (cs.SI)
paper · pdf · doi:10.48550/arxiv.2205.08028
openalex publication_date 2022/05/16 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Hyperbolic geometry offers a natural focus + context for data visualization and has been shown to underlie real-world complex networks. However, current hyperbolic network visualization approaches are limited to special types of networks and do not scale to large datasets. With this in mind, we designed, implemented, and analyzed three methods for hyperbolic visualization of networks in the browser based on inverse projections, generalized force-directed algorithms, and hyperbolic multi-dimensional scaling (H-MDS). A comparison with Euclidean MDS shows that H-MDS produces embeddings with lower distortion for several types of networks. All three methods can handle node-link representations and are available in fully functional web-based systems.