Effects of Alternative Scatterplot Designs on Belief

Viewers tend to underestimate correlation in positively correlated scatterplots. However, systematically changing the size and opacity of scatterplot points can bias estimates upwards, correcting for this underestimation. Here, we examine whether the application of these visualisation techniques goes beyond a simple perceptual effect and could actually influence beliefs about information from trusted news sources. We present a fully-reproducible study in which we demonstrate that scatterplot manipulations that are able to correct for the correlation underestimation bias can also induce stronger levels of belief change compared to conventional scatterplots presenting identical data. Consequently, we show that novel visualisation techniques can be used to drive belief change, and suggest future directions for extending this work with regards to altering attitudes and behaviours.

Authors

Institutions

Publication Details

Published
2025-04-24
DOI
https://doi.org/10.1145/3706598.3713809
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
1.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effects of Alternative Scatterplot Designs on Belief

Gabriel Strain, Andrew Stewart, Charlotte Rutherford, Caroline Jay et al.
1 citations
Data Visualization and Analytics
1.28
article

Effects of Alternative Scatterplot Designs on Belief

Gabriel Strain, Andrew Stewart, Charlotte Rutherford, Caroline Jay, Paul A. Warren
article en
1 citations

Abstract

Viewers tend to underestimate correlation in positively correlated scatterplots. However, systematically changing the size and opacity of scatterplot points can bias estimates upwards, correcting for this underestimation. Here, we examine whether the application of these visualisation techniques goes beyond a simple perceptual effect and could actually influence beliefs about information from trusted news sources. We present a fully-reproducible study in which we demonstrate that scatterplot manipulations that are able to correct for the correlation underestimation bias can also induce stronger levels of belief change compared to conventional scatterplots presenting identical data. Consequently, we show that novel visualisation techniques can be used to drive belief change, and suggest future directions for extending this work with regards to altering attitudes and behaviours.

Manchester Academic Health Science Centre (GB), University of Manchester (GB)
Openalex Percentile: Top 21%
Data Visualization and Analytics
1.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.