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
Exemplar figure, described by caption below
An illustrative of our experiments. Participants rated various visualizations on FAMILIARITY, CLARITY, CREDIBILITY, RELIABILITY, and CONFIDENCE, exploring their alignment with visual features and trust ratings.
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Human-centered computing, Trust, Visualization, Visualization design and evaluation methods


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.