  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.
