Prior research suggests that perceived transparency is often associated with perceived trust. For some data types, greater transparency in data visualization is also associated with an increase in the amount of information depicted. Based on prior work in economics and political science that has identified four dimensions of transparency, we examined the influence of accuracy, clarity, amount of disclosure, and thoroughness on a decision task where participants relied on map-based visualizations with varying complexity to solve a crisis. The results of our preliminary analysis suggest that perceived clarity, amount of disclosure. and thoroughness significantly predicted individuals' selection of a Google Maps-like application with either less information or more information. Trust and perceived accuracy did not significantly predict which navigation application visualization participants decided to use (i.e., one with more information or less information). Further, our preliminary results suggest that an individual's ratings of accuracy and disclosure of a visualization predicted their ratings of the trustworthiness of that visualization. We discuss the implications of a possible dissociation between trust and decision tasks on visualization evaluation. In future work, we aim to examine the influence of the amount of information shown in a visualization on ratings of trust and determine the generalizability of our preliminary findings to different task types and visualization approaches.

CCS Concepts: Human-centered computing --> Laboratory experiments; HCI theory, concepts and models; Empirical studies in HCI

Cindy Xiong, Lace M. K. Padilla, Kent Grayson, and Steven Franconeri

EuroVis Workshop on Trustworthy Visualization (TrustVis)

Papers

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