Visualizing network data is applicable in domains such as biology, engineering, and social sciences. We report the results of a study comparing the effectiveness of the two primary techniques for showing network data: node-link diagrams and adjacency matrices. Specifically, an evaluation with a large number of online participants revealed statistically significant differences between the two visualizations. Our work adds to existing research in several ways. First, we explore a broad spectrum of network tasks, many of which had not been previously evaluated. Second, our study uses a large dataset, typical of many real-life networks not explored by previous studies. Third, we leverage crowdsourcing to evaluate many tasks with many participants.
@article{arxiv.1709.00293,
title = {Revisited Experimental Comparison of Node-Link and Matrix Representations},
author = {Mershack Okoe and Radu Jianu and Stephen Kobourov},
journal= {arXiv preprint arXiv:1709.00293},
year = {2017}
}