Vistrust: a Multidimensional Framework and Empirical Study of Trust in Data Visualizations

Hamza Elhamdadi, Adam Stefkovics, Johanna Beyer, Eric Moerth, Hanspeter Pfister, Cindy Xiong Bearfield, Carolina Nobre

Room: 109

2023-10-25T00:45:00ZGMT-0600Change your timezone on the schedule page
Exemplar figure, described by caption below
An integrated framework, which outlines the development of trust in visualizations. The framework defines the different trust antecedents of the two basic components of trust (cognitive and affective trust). Both cognitive and affective trust can relate to the visualization and the underlying data. Individual characteristics can play a role in shaping one's level of trust in visualizations, and behavioral outcomes can emerge as a results of trust judgements.
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Trust, visualization, science, framework


Trust is an essential aspect of data visualization, as it plays a crucial role in the interpretation and decision-making processes of users. While research in social sciences outlines the multi-dimensional factors that can play a role in trust formation, most data visualization trust researchers employ a single-item scale to measure trust. We address this gap by proposing a comprehensive, multidimensional conceptualization and operationalization of trust in visualization. We do this by applying general theories of trust from social sciences, as well as synthesizing and extending earlier work and factors identified by studies in the visualization field. We apply a two-dimensional approach to trust in visualization, to distinguish between cognitive and affective elements, as well as between visualization and data-specific trust antecedents. We use our framework to design and run a large crowd-sourced study to quantify the role of visual complexity in establishing trust in science visualizations. Our study provides empirical evidence for several aspects of our proposed theoretical framework, most notably the impact of cognition, affective responses, and individual differences when establishing trust in visualizations.