Offsetting Perceptual Bias in Visual Clustering: The Role of Point Size Adjustment in Variable Display Sizes

TL;DR

This paper investigates how scatterplot size influences perceived clustering patterns and demonstrates that adjusting point sizes can effectively offset perceptual biases caused by display size variations.

Contribution

It introduces a method to counteract perceptual bias in scatterplots by adjusting point sizes, enhancing accuracy in visual cluster analysis across different display sizes.

Findings

Scatterplot size significantly affects cluster perception.

Adjusting point sizes mitigates perceptual bias.

Method improves consistency in visual clustering analysis.

Abstract

Scatterplots are frequently shared across different displays in collaborative and communicative visual analytics. However, variations in displays diversify scatterplot sizes. Such variations can influence the perception of clustering patterns, introducing potential biases leading to misinterpretations in cluster analysis. In this research, we explore how scatterplot size affects cluster assignment and investigate how we can offset such bias. We first conduct a controlled study asking participants to perform visual clustering on scatterplots of varying sizes. We found that changes in scatterplot size significantly alter cluster perception in three key features. In our subsequent experiment, we examine how adjusting point sizes can mitigate this bias. As a result, we verify that adjusting point size can effectively counteract the perceptual biases caused by varying scatterplot sizes. We wrap up our research by discussing the necessity and applicability of our findings in realworld applications.