信息可视化中强调效应的基线研究

Aristides Mairena, M. Dechant, C. Gutwin, A. Cockburn
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引用次数: 5

摘要

强调效果——使某些元素更加突出的视觉变化——通常用于信息可视化,以吸引用户的注意力或表明重要性。虽然存在强调的理论框架(通过视觉突出与背景元素的比较,将视觉上不同的强调效果联系起来),但预测用户如何感知强调效果的大多数指标都来自人类视觉的抽象模型,这可能不适用于可视化设计。特别是,设计师在设计可视化时,很难知道不同的强调效果将如何比较,以及如何确保一种效果的用户体验与另一种效果相似。为了解决这一差距,我们进行了两项研究,提供了关于用户如何感知不同强调效果的经验证据,使用了三个视觉变量(颜色、大小和模糊/聚焦)和八个强度水平。在我们的第一项研究中,凝视跟踪、鼠标点击和主观反应的结果表明,不同类型的影响和不同水平之间存在显著差异。我们的第二项研究测试了来自MASSVIS数据集的逼真可视化效果,并看到了类似的结果。我们根据第一项研究的数据建立了一个简单的预测模型,并用它来预测第二项研究的结果;该模型是准确的,预测与实际值之间具有高度相关性。我们的研究和经验模型为想要了解用户如何感知强调效果的设计师提供了新的信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Baseline Study of Emphasis Effects in Information Visualization
Emphasis effects – visual changes that make certain elements more prominent – are commonly used in information visualization to draw the user’s attention or to indicate importance. Although theoretical frameworks of emphasis exist (that link visually diverse emphasis effects through the idea of visual prominence compared to background elements), most metrics for predicting how emphasis effects will be perceived by users come from abstract models of human vision which may not apply to visualization design. In particular, it is difficult for designers to know, when designing a visualization, how different emphasis effects will compare and how to ensure that the user’s experience with one effect will be similar to that with another. To address this gap, we carried out two studies that provide empirical evidence about how users perceive different emphasis effects, using three visual variables (colour, size, and blur/focus) and eight strength levels. Results from gaze tracking, mouse clicks, and subjective responses in our first study show that there are significant differences between different kinds of effects and between levels. Our second study tested the effects in realistic visualizations taken from the MASSVIS dataset, and saw similar results. We developed a simple predictive model from the data in our first study, and used it to predict the results in the second; the model was accurate, with high correlations between predictions and real values. Our studies and empirical models provide new information for designers who want to understand how emphasis effects will be perceived by users.
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