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寻求平衡:整合文本与图表时读者的收获与偏好

Striking a Balance: Reader Takeaways and Preferences when Integrating Text and Charts.

作者信息

Stokes Chase, Setlur Vidya, Cogley Bridget, Satyanarayan Arvind, Hearst Marti A

出版信息

IEEE Trans Vis Comput Graph. 2023 Jan;29(1):1233-1243. doi: 10.1109/TVCG.2022.3209383. Epub 2022 Dec 16.

Abstract

While visualizations are an effective way to represent insights about information, they rarely stand alone. When designing a visualization, text is often added to provide additional context and guidance for the reader. However, there is little experimental evidence to guide designers as to what is the right amount of text to show within a chart, what its qualitative properties should be, and where it should be placed. Prior work also shows variation in personal preferences for charts versus textual representations. In this paper, we explore several research questions about the relative value of textual components of visualizations. 302 participants ranked univariate line charts containing varying amounts of text, ranging from no text (except for the axes) to a written paragraph with no visuals. Participants also described what information they could take away from line charts containing text with varying semantic content. We find that heavily annotated charts were not penalized. In fact, participants preferred the charts with the largest number of textual annotations over charts with fewer annotations or text alone. We also find effects of semantic content. For instance, the text that describes statistical or relational components of a chart leads to more takeaways referring to statistics or relational comparisons than text describing elemental or encoded components. Finally, we find different effects for the semantic levels based on the placement of the text on the chart; some kinds of information are best placed in the title, while others should be placed closer to the data. We compile these results into four chart design guidelines and discuss future implications for the combination of text and charts.

摘要

虽然可视化是呈现信息见解的有效方式,但它们很少单独存在。在设计可视化时,通常会添加文本以为读者提供更多背景信息和指导。然而,几乎没有实验证据能指导设计师在图表中展示多少文本才合适、文本的定性属性应该是什么以及文本应该放在哪里。先前的研究还表明,人们对图表和文本表述的个人偏好存在差异。在本文中,我们探讨了几个关于可视化文本组件相对价值的研究问题。302名参与者对包含不同数量文本的单变量折线图进行了排序,文本数量从无文本(除坐标轴外)到一段没有视觉元素的文字不等。参与者还描述了他们能从包含不同语义内容文本的折线图中获取哪些信息。我们发现注释丰富的图表并未受到惩罚。事实上,与注释较少或仅有文本的图表相比,参与者更喜欢文本注释最多的图表。我们还发现了语义内容的影响。例如,描述图表统计或关系组件的文本比描述基本或编码组件的文本能带来更多关于统计或关系比较的信息。最后,基于文本在图表上的位置,我们发现了语义层次的不同影响;有些信息最好放在标题中,而其他信息则应更靠近数据放置。我们将这些结果整理成四条图表设计指南,并讨论了文本与图表结合的未来意义。

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