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This work investigates and compares the performance of node-link diagrams,adjacency matrices, and bipartite layouts for visualizing networks. In acrowd-sourced user study (n = 150), we measure the task accuracy and completiontime 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 largeand directed networks. We consider three overview tasks on networks with 500nodes: (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 forrevealing the overall network structure, while adjacency matrices are mostreliable across the different tasks.

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