Characterizing Visualization Perception with Psychological Phenomena: Uncovering the Role of Subitizing in Data Visualization

TL;DR

This study investigates how psychological phenomena, specifically subitizing, influence the perception of categorical data visualizations, providing empirical evidence to inform visualization design guidelines.

Contribution

It introduces an experimental framework linking psychological subitizing effects to visualization task performance, bridging heuristic guidelines and empirical data.

Findings

Performance is high for fewer than six categories across tasks

Increasing categories reduces performance depending on task and encoding

Empirical evidence supports subitizing's role in visualization perception

Abstract

Understanding how people perceive visualizations is crucial for designing effective visual data representations; however, many heuristic design guidelines are derived from specific tasks or visualization types, without considering the constraints or conditions under which those guidelines hold. In this work, we aimed to assess existing design heuristics for categorical visualization using well-established psychological knowledge. Specifically, we examine the impact of the subitizing phenomenon in cognitive psychology -- people's ability to automatically recognize a small set of objects instantly without counting -- in data visualizations. We conducted three experiments with multi-class scatterplots -- between 2 and 15 classes with varying design choices -- across three different tasks -- class estimation, correlation comparison, and clustering judgments -- to understand how performance changes as the number of classes (and therefore set size) increases. Our results indicate if the category number is smaller than six, people tend to perform well at all tasks, providing empirical evidence of subitizing in visualization. When category numbers increased, performance fell, with the magnitude of the performance change depending on task and encoding. Our study bridges the gap between heuristic guidelines and empirical evidence by applying well-established psychological theories, suggesting future opportunities for using psychological theories and constructs to characterize visualization perception.