Effects of Point Size and Opacity Adjustments in Scatterplots

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Abstract

Systematically changing the size and opacity of points on scatterplots can be used to induce more accurate perceptions of correlation by viewers. Evidence points to the mechanisms behind these effects being similar, so one may expect their combination to be additive regarding their effects on correlation estimation. We present a fully-reproducible study in which we combine techniques for influencing correlation perception to show that in reality, effects of changing point size and opacity interact in a non-additive fashion. We show that there is a great deal of scope for using visual features to change viewers’ perceptions of data visualizations. Additionally, we use our results to further interrogate the perceptual mechanisms at play when changing point size and opacity in scatterplots.
Original languageEnglish
Publication statusAccepted/In press - 11 Mar 2024
EventThe ACM (Association of Computing Machinery) CHI conference on Human Factors in Computing Systems - Hawaii
Duration: 11 May 202416 May 2024
https://chi2024.acm.org

Conference

ConferenceThe ACM (Association of Computing Machinery) CHI conference on Human Factors in Computing Systems
Abbreviated titleCHI 2024
Period11/05/2416/05/24
Internet address

Keywords

  • correlation
  • scatterplot
  • perception
  • crowdsourced

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