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

TL;DR

This study investigates how visual design elements and data characteristics in visualizations evoke emotional responses, revealing that both design choices and data features influence viewer emotions even when data is meaningless.

Contribution

It provides empirical evidence on the impact of specific visualization elements and data features on emotional responses, offering guidelines for design to manage emotional impact.

Findings

Color, chart type, data trend, variability, and density affect emotion.

Certain data features influence emotion even without data meaning.

Design guidelines for balancing emotional impact.

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.