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
- Gabriel Strain (ORCID: https://orcid.org/0000-0002-4769-9221)
- Andrew Stewart (ORCID: https://orcid.org/0000-0002-9795-4104)
- Charlotte Rutherford (ORCID: https://orcid.org/0000-0003-2733-2323)
- Caroline Jay (ORCID: https://orcid.org/0000-0002-6080-1382)
- Paul A. Warren (ORCID: https://orcid.org/0000-0002-4071-7650)
Institutions
- Manchester Academic Health Science Centre (GB)
- University of Manchester (GB)
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