Uncertain About Uncertainty: How Qualitative Expressions of Forecaster Confidence Impact Decision-Making With Uncertainty Visualizations.

When forecasting events, multiple types of uncertainty are often inherently present in the modeling process. Various uncertainty typologies exist, and each type of uncertainty has different implications a scientist might want to convey. In this work, we focus on one type of distinction between and .

Factors Predicting Willingness to Share COVID-19 Misinformation.

We conducted a preregistered exploratory survey to assess whether patterns of individual differences in political orientation, social dominance orientation (SDO), traditionalism, conspiracy ideation, or attitudes about science predict willingness to share different kinds of misinformation regarding the COVID-19 pandemic online. Analyses revealed two orthogonal models of individual differences predicting the willingness to share misinformation over social media platforms. Both models suggest a sizable role of different aspects of political belief, particularly SDO, in predicting tendencies to share different kinds of misinformation, predominantly conspiracy theories.

The powerful influence of marks: Visual and knowledge-driven processing in hurricane track displays.

Given the widespread use of visualizations to communicate hazard risks, forecast visualizations must be as effective to interpret as possible. However, despite incorporating best practices, visualizations can influence viewer judgments in ways that the designers did not anticipate. Visualization designers should understand the full implications of visualization techniques and seek to develop visualizations that account for the complexities in decision-making.

Toward Objective Evaluation of Working Memory in Visualizations: A Case Study Using Pupillometry and a Dual-Task Paradigm.

Cognitive science has established widely used and validated procedures for evaluating working memory in numerous applied domains, but surprisingly few studies have employed these methodologies to assess claims about the impacts of visualizations on working memory. The lack of information visualization research that uses validated procedures for measuring working memory may be due, in part, to the absence of cross-domain methodological guidance tailored explicitly to the unique needs of visualization research. This paper presents a set of clear, practical, and empirically validated methods for evaluating working memory during visualization tasks and provides readers with guidance in selecting an appropriate working memory evaluation paradigm.