Visualizing undirected graphs and symmetric square matrices as overlapping sets

摘要

Undirected graphs and symmetric square matrices are frequently found in various domains. An example is character co-occurrence matrices in digital humanities. However, the visualization of these datasets is difficult, especially if the graph is highly connected. In this article, we propose a method for visualizing undirected graphs and symmetric square matrices, by transforming them into overlapping sets, and then by visualizing these overlapping sets using set visualization techniques such as Euler diagram or rainbow boxes. We also propose a clustering approach to simplify the visualization. We apply this method to the visualization of various character co-occurrence matrices extracted from novels or DBpedia, ranging from 21 to 114 characters. We show that this visualization allows the finding of several interesting insights. Finally, we discuss the advantages and drawbacks of this method, and we compare it to other approaches in the literature.