Node-link or adjacency matrices: Old question, New Insights

Mershack Okoe, Radu Jianu, Stephen Kobourov

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

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 two large datasets, typical of many real-life networks not explored by previous studies. Third, we leverage crowdsourcing to evaluate many tasks with many participants. This paper is an expanded journal version of a Graph Drawing (GD'17) conference paper. We evaluated a second dataset, added a qualitative feedback section, and expanded the procedure, results, discussion, and limitations sections.

Original languageEnglish (US)
Article number8438968
Pages (from-to)2940-2952
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Volume25
Issue number10
DOIs
StatePublished - Oct 1 2019

Keywords

  • Evaluation
  • adjacency matrices
  • graphs
  • networks
  • node-link
  • user study

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design

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