Affective Congruence in Visualization Design: Influences on Reading Categorical Maps

Recent work in data visualization has demonstrated that small, perceptually-distinct color palettes such as those used in categorical mapping can connote significant affective qualities. Data that are mapped or otherwise visualized are also often emotive in nature, either inherently (e.g., climate change, disease mortality rates), or by design, such as can be found in visual storytelling. However, little is known about how the affective qualities of color interact with those of data context in visualization design. This paper describes the results of a crowdsourced study on the influence of affectively congruent versus incongruent color schemes on categorical map-reading response. We report both objective (pattern detection; area comparison) and subjective (affective quality; appropriateness; preference) measures of map-reader response. Our results suggest that affectively congruent colors amplify perceptions of the affective qualities of maps with emotive topics, affective incongruence may cause confusion, and that affective congruence is particularly influential in maps of positive-leaning data topics. Finally, we offer preliminary design recommendations for balancing color congruence with other design factors, and for synthesizing color and affective context in thematic map design.

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Files

Metadata

Work Title Affective Congruence in Visualization Design: Influences on Reading Categorical Maps
Access
Open Access
Creators
  1. Cary L. Anderson
  2. Anthony C. Robinson
Keyword
  1. Color
  2. Visualization
  3. Emotion
  4. Design
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. IEEE Transactions on Visualization and Computer Graphics
Publication Date January 8, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1109/TVCG.2021.3050118
Deposited May 22, 2023

Versions

Analytics

Collections

This resource is currently not in any collection.

Work History

Version 1
published

  • Created
  • Added Anderson_Robinson_2020.pdf
  • Added Creator Cary L. Anderson
  • Added Creator Anthony C. Robinson
  • Published
  • Updated Keyword, Publication Date Show Changes
    Keyword
    • Color, Visualization, Emotion, Design
    Publication Date
    • 2021-01-01
    • 2021-01-08
  • Updated