Isaac Cho

TL;DR: This paper presents a novel, systematic study and resulting analyses that investigate the effects of anchoring effect on human decision-making using visual analytic systems, and describes detailed analyses of users’ interaction logs which reveal the impact of Anchoring bias on the visual representation preferred and paths of analysis.

TL;DR: This work categorizes Financial systems in terms of data sources, applied automated techniques, visualization techniques, interaction, and evaluation methods, and presents task requirements extracted from interviews with domain experts in order to help researchers design better systems with detailed goals.

TL;DR: VAiRoma is a visual analytics system that couples state-of-the-art text analysis methods with an intuitive visual interface to help users make sense of events, places, times, and more importantly, the relationships between them and allows users to learn and create new knowledge regarding Roman history in an informed way.

TL;DR: It is revealed that the presence of conflicting information, presented to users in the form of cues, impacts the ability to judge the veracity of news in systematic ways and has the potential to inform the design of visual analytics systems so that they may be used to mitigate the effects of cognitive biases and stymie the spread of misinformation on social media.

TL;DR: A novel visual text analytics system that connects categorical data (demographic information) with textual data, allowing users to understand the characteristics of different demographic groups in a transparent and exploratory manner, and reports results from a comparative evaluation, showing that the DemographicVis is quantitatively superior or competitive and subjectively preferred when compared to a commercial text analysis tool.