The Perception of Graph Properties in Graph Layouts

Utkarsh Soni, Yafeng Lu, Brett Hansen, Helen C. Purchase, Stephen Kobourov, Ross Maciejewski

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)169-181
Number of pages13
JournalComputer Graphics Forum
Issue number3
StatePublished - Jun 2018
Externally publishedYes

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design


Dive into the research topics of 'The Perception of Graph Properties in Graph Layouts'. Together they form a unique fingerprint.

Cite this