Demo Data from EDBT 2026 / reviewers in the wild / expert
Charlotte Rutherford
dblp:402/9121
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0003-2733-2323ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer graphics and multimedia
1 paper |
Visualization and visual analytics · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Visualization and visual analytics › graphical perception
correlation perception |
0.9 | 1 | 2025 | Effects of Alternative Scatterplot Designs on Belief · CHI 2025 |
Visualization and visual analytics › scatterplot
scatterplot design |
0.9 | 1 | 2025 | Effects of Alternative Scatterplot Designs on Belief · CHI 2025 |
Methods — techniques the papers use, named apart from their topics
reproducible study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Effects of Alternative Scatterplot Designs on BeliefabstractViewers 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. Gabriel Strain, Andrew J. Stewart, Caroline Jay, Charlotte Rutherford |
CHI | 4 |