Quantifying Emotional Responses to Immutable Data Characteristics and Designer Choices in Data Visualizations

TL;DR

This study investigates how emotion is elicited by immutable data characteristics (data trend, variance, density) and designer choices (color, chart type) in data visualizations. Using five crowdsourced studies and Self-Assessment Manikin (SAM) ratings, it shows that color has the strongest influence on arousal and valence, with chart type, trend, variance, and density also modulating emotional responses even when data carry no semantic meaning. The work provides practical guidelines for leveraging color, scale, and chart type to counterbalance or emphasize the emotional impact of immutable data characteristics, and discusses limitations such as the absence of semantic content, cultural effects, and task-based performance considerations. The findings advance understanding of affective design in visualization and offer a framework for designing visuals that balance emotion with accurate data interpretation in real-world contexts.

Abstract

Emotion is an important factor to consider when designing visualizations as it can impact the amount of trust viewers place in a visualization, how well they can retrieve information and understand the underlying data, and how much they engage with or connect to a visualization. We conducted five crowdsourced experiments to quantify the effects of color, chart type, data trend, data variability and data density on emotion (measured through self-reported arousal and valence). Results from our experiments show that there are multiple design elements which influence the emotion induced by a visualization and, more surprisingly, that certain data characteristics influence the emotion of viewers even when the data has no meaning. In light of these findings, we offer guidelines on how to use color, scale, and chart type to counterbalance and emphasize the emotional impact of immutable data characteristics.

Figures (24)

• Figure 1: SAM scales used in our studies (figures from betella2016affective).
• Figure 2: Workflow for the five studies. Dashed blocks are optional question(s) asked depending on each study design. Measurements 1 and 2 are arousal or valence, depending on the counter-balanced order.
• Figure 3: Color palettes used in S1.
• Figure 4: Mean results for each color palette for S1, centered on a neutral value of $5$.
• Figure 5: One set of charts for all 9 conditions used in S2 (three data trends and three color palettes).