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Trust is an essential aspect of data visualization, as it plays a crucialrole in the interpretation and decision-making processes of users. Whileresearch in social sciences outlines the multi-dimensional factors that canplay a role in trust formation, most data visualization trust researchersemploy a single-item scale to measure trust. We address this gap by proposing acomprehensive, multidimensional conceptualization and operationalization oftrust in visualization. We do this by applying general theories of trust fromsocial sciences, as well as synthesizing and extending earlier work and factorsidentified by studies in the visualization field. We apply a two-dimensionalapproach to trust in visualization, to distinguish between cognitive andaffective elements, as well as between visualization and data-specific trustantecedents. We use our framework to design and run a large crowd-sourced studyto quantify the role of visual complexity in establishing trust in sciencevisualizations. Our study provides empirical evidence for several aspects ofour proposed theoretical framework, most notably the impact of cognition,affective responses, and individual differences when establishing trust invisualizations.

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