Do You Trust What You See? Toward A Multidimensional Measure of Trust in Visualization

被引:0
|
作者
Pandey, Saugat [1 ]
McKinley, Oen G. [1 ]
Crouser, R. Jordan [2 ]
Ottley, Alvitta [1 ]
机构
[1] Washington Univ St Louis, St Louis, MO 63130 USA
[2] Smith Coll, Northampton, MA 01063 USA
基金
美国国家科学基金会;
关键词
Human-centered computing; Visualization; Visualization design and evaluation methods; INDIVIDUAL-DIFFERENCES; TRUSTWORTHINESS; COMMITMENT; ACCEPTANCE;
D O I
10.1109/VIS54172.2023.00014
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:26 / 30
页数:5
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