Browsing by Author "Cho, Isaac"

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    Investigating Effects of Visual Anchors on Decision-Making about Misinformation
    (The Eurographics Association and John Wiley & Sons Ltd., 2019) Wesslen, Ryan; Santhanam, Sashank; Karduni, Alireza; Cho, Isaac; Shaikh, Samira; Dou, Wenwen; Gleicher, Michael and Viola, Ivan and Leitte, Heike
    Cognitive biases are systematic errors in judgment due to an over-reliance on rule-of-thumb heuristics. Recent research suggests that cognitive biases, like numerical anchoring, transfers to visual analytics in the form of visual anchoring. However, it is unclear how visualization users can be visually anchored and how the anchors affect decision-making. To investigate, we performed a between-subjects laboratory experiment with 94 participants to analyze the effects of visual anchors and strategy cues using a visual analytics system. The decision-making task was to identify misinformation from Twitter news accounts. Participants were randomly assigned to conditions that modified the scenario video (visual anchor) and/or strategy cues provided. Our findings suggest that such interventions affect user activity, speed, confidence, and, under certain circumstances, accuracy. We discuss implications of our results on the forking paths problem and raise concerns on how visualization researchers train users to avoid unintentionally anchoring users and affecting the end result.
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    PDViz: A Visual Analytics Approach for State Policy Data
    (Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Han, Dongyun; Nayeem, Abdullah‐Al‐Raihan; Windett, Jason; Cho, Isaac; Hauser, Helwig and Alliez, Pierre
    Sub‐national governments across the United States implement a variety of policies to address large societal problems and needs. Many policies are picked up or adopted in other states. This process is called policy diffusion and allows researchers to analyse and compare the social, political, and contextual characteristics that lead to adopting certain policies, as well as the efficacy of these policies once adopted. In this paper, we introduce PDViz, a visual analytics approach that allows social scientists to dynamically analyse the policy diffusion history and underlying patterns. It is designed for analysing and answering a list of research questions and tasks posed by social scientists in prior work. To evaluate our system, we present two usage scenarios and conduct interviews with domain experts in political science. The interviews highlight that PDViz provides the result of policy diffusion patterns that align with their domain knowledge as well as the potential to be a learning tool for students to understand the concept of policy diffusion.