Perception of symmetries in drawings of graphs

Felice De Luca, Stephen G Kobourov, Helen Purchase

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Symmetry is an important factor in human perception in general, as well as in the visualization of graphs in particular. There are three main types of symmetry: reflective, translational, and rotational. We report the results of a human subjects experiment to determine what types of symmetries are more salient in drawings of graphs. We found statistically significant evidence that vertical reflective symmetry is the most dominant (when selecting among vertical reflective, horizontal reflective, and translational). We also found statistically significant evidence that rotational symmetry is affected by the number of radial axes (the more, the better), with a notable exception at four axes.

Original languageEnglish (US)
Title of host publicationGraph Drawing and Network Visualization - 26th International Symposium, GD 2018, Proceedings
EditorsTherese Biedl, Andreas Kerren
PublisherSpringer-Verlag
Pages433-446
Number of pages14
ISBN (Print)9783030044138
DOIs
StatePublished - Jan 1 2018
Event26th International Symposium on Graph Drawing and Network Visualization, GD 2018 - Barcelona, Spain
Duration: Sep 26 2018Sep 28 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11282 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other26th International Symposium on Graph Drawing and Network Visualization, GD 2018
CountrySpain
CityBarcelona
Period9/26/189/28/18

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

De Luca, F., Kobourov, S. G., & Purchase, H. (2018). Perception of symmetries in drawings of graphs. In T. Biedl, & A. Kerren (Eds.), Graph Drawing and Network Visualization - 26th International Symposium, GD 2018, Proceedings (pp. 433-446). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11282 LNCS). Springer-Verlag. https://doi.org/10.1007/978-3-030-04414-5_31