New Quality Metrics for Dynamic Graph Drawing [article]

Amyra Meidiana, Seok-Hee Hong, Peter Eades
2020 arXiv   pre-print
In this paper, we present new quality metrics for dynamic graph drawings. Namely, we present a new framework for change faithfulness metrics for dynamic graph drawings, which compare the ground truth change in dynamic graphs and the geometric change in drawings. More specifically, we present two specific instances, cluster change faithfulness metrics and distance change faithfulness metrics. We first validate the effectiveness of our new metrics using deformation experiments. Then we compare
more » ... ious graph drawing algorithms using our metrics. Our experiments confirm that the best cluster (resp. distance) faithful graph drawing algorithms are also cluster (resp. distance) change faithful.
arXiv:2008.07764v2 fatcat:h4j7ucynxrcpbik72fbrighrgq