The perception of graph properties in graph layouts

Soni, U., Lu, Y., Hansen, B., Purchase, H. , Kobourov, S. and Maciejewski, R. (2018) The perception of graph properties in graph layouts. Computer Graphics Forum, 37(3), pp. 169-181. (doi: 10.1111/cgf.13410)

Abstract

When looking at drawings of graphs, questions about graph density, community structures, local clustering and other graph properties may be of critical importance for analysis. While graph layout algorithms have focused on minimizing edge crossing, symmetry, and other such layout properties, there is not much known about how these algorithms relate to a user’s ability to perceive graph properties for a given graph layout. In this study, we apply previously established methodologies for perceptual analysis to identify which graph drawing layout will help the user best perceive a particular graph property. We conduct a large scale (n = 588) crowdsourced experiment to investigate whether the perception of two graph properties (graph density and average local clustering coefficient) can be modeled using Weber’s law. We study three graph layout algorithms from three representative classes (Force Directed FD, Circular, and Multi-Dimensional Scaling MDS), and the results of this experiment establish the precision of judgment for these graph layouts and properties. Our findings demonstrate that the perception of graph density can be modeled with Weber’s law. Furthermore, the perception of the average clustering coefficient can be modeled as an inverse of Weber’s law, and the MDS layout showed a significantly different precision of judgment than the FD layout.

• Item Type: Articles
• Additional Information: Paper presented at 20th IEEE Eurographics Conference on Visualization (EuroVis), 2018, Brno, Czech Republic, 4-8 June 2018. This work was supported in part by the U.S. Department of Homeland Security’s CAOE, Award 2017-ST-061-QA0001-01 and the National Science Foundation, Grant Nos. 1639227, 1712119, and 1740858.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Purchase, Dr Helen
• Authors: Soni, U., Lu, Y., Hansen, B., Purchase, H., Kobourov, S., and Maciejewski, R.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Computer Graphics Forum
• Publisher: Wiley
• ISSN: 0167-7055
• ISSN (Online): 1467-8659
• Published Online: 10 July 2018
• Copyright Holders: Copyright © 2018 The Author(s) Computer Graphics Forum ©2018 The Eurographics Association and John Wiley and Sons Ltd
• First Published: First published in Computer Graphics Forum 37(3):169-181
• Publisher Policy: Reproduced in accordance with the publisher copyright policy