Cited by 212Data Visualization and AnalyticsComputer Graphics and Visualization TechniquesVisual perception and processing mechanisms

Ranking Visualizations of Correlation Using Weber's Law

Harrison, Lane, Yang, Fumeng, Franconeri, Steven, Chang, Remco·2014·IEEE Transactions on Visualization and Computer Graphics

Abstract

Despite years of research yielding systems and guidelines to aid visualization design, practitioners still face the challenge of identifying the best visualization for a given dataset and task. One promising approach to circumvent this problem is to leverage perceptual laws to quantitatively evaluate the effectiveness of a visualization design. Following previously established methodologies, we conduct a large scale (n=1687) crowdsourced experiment to investigate whether the perception of correlation in nine commonly used visualizations can be modeled using Weber's law. The results of this experiment contribute to our understanding of information visualization by establishing that: (1) for all tested visualizations, the precision of correlation judgment could be modeled by Weber's law, (2) correlation judgment precision showed striking variation between negatively and positively correlated data, and (3) Weber models provide a concise means to quantify, compare, and rank the perceptual precision afforded by a visualization.

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Crossref · 10.1109/tvcg.2014.2346979

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Authors
Harrison, L., Yang, F., Franconeri, S., & Chang, R.
Affiliations
  • Tufts University (US)
  • Northwestern University (US)
Venue
IEEE Transactions on Visualization and Computer Graphics
Published
2014-12-31
Volume
20
Issue
12
Pages
1943-1952
ISSN
1077-2626 (ISSN-L)
OpenAlex
W2043523210
Cited by
212
References
29
Citations by year
2026: 7 · 2025: 15 · 2024: 20 · 2023: 22 · 2022: 17 · 2021: 25 · 2020: 20 · 2019: 20 · 2018: 22 · 2017: 20 · 2016: 17 · 2015: 6 · 2014: 1
FWCI
13.12
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Visualization and Computer Graphics (publishedVersion)
  • PubMed (publishedVersion)
Funders
NSF (IIS-1218170)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Computer Graphics and Visualization Techniques
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
Keywords
correlation visualization, Weber's law, perceptual precision, perceptual models, negative correlation, positive correlation, crowdsourced experiments

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