Do You Trust What You See? Toward A Multidimensional Measure of Trust in Visualization
Saugat Pandey, Oen G McKinley, R. Jordan Crouser, Alvitta Ottley
Room: 104
2023-10-24T22:36:00ZGMT-0600Change your timezone on the schedule page
2023-10-24T22:36:00Z
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Keywords
Human-centered computing, Trust, Visualization, Visualization design and evaluation methods
Abstract
Few concepts are as ubiquitous in computational fields as trust. However, in the case of information visualization, there are several unique and complex challenges, chief among them: defining and measuring trust. In this paper, we investigate the factors that influence trust in visualizations. We draw on the literature to identify five factors likely to affect trust: credibility, clarity, reliability, familiarity, and confidence. We then conduct two studies investigating these factors' relationship with visualization design features. In the first study, participants' credibility, understanding, and reliability ratings depended on the visualization design and its source. In the second study, we find these factors also align with subjective trust rankings. Our findings suggest that these five factors are important considerations for the design of trustworthy visualizations.