Comparative Evaluation of Bipartite, Node-Link, and Matrix-Based Network Representations

IEEE Transactions on Visualization and Computer Graphics, vol. 29, pp. 1–11

Abstract

This work investigates and compares the performance of node-link diagrams, adjacency matrices, and bipartite layouts for visualizing networks. In a crowd-sourced user study ( n=150), we measure the task accuracy and completion time of the three representations for different network classes and properties. In contrast to the literature, which covers mostly topology-based tasks (e.g., path finding) in small datasets, we mainly focus on overview tasks for large and directed networks. We consider three overview tasks on networks with 500 nodes: (T1) network class identification, (T2) cluster detection, and (T3) network density estimation, and two detailed tasks: (T4) node in-degree vs. out-degree and (T5) representation mapping, on networks with 50 and 20 nodes, respectively. Our results show that bipartite layouts are beneficial for revealing the overall network structure, while adjacency matrices are most reliable across the different tasks.

Authors 6

1. Moataz Abdelaal

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart, Germany

2. Nathan Daniel Schiele Aachen

   Leiden University

   Affiliation as printed

   Leiden University, Netherlands

3. Katrin Angerbauer

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart, Germany

4. Kuno Kurzhals

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart, Germany

5. Michael Sedlmair

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart, Germany

6. Daniel Weiskopf

   University of Stuttgart

   Affiliation as printed

   University of Stuttgart, Germany