论文标题

达到平衡:集成文本和图表时的读者外卖和偏好

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

论文作者

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

论文摘要

尽管可视化是表示有关信息见解的有效方法,但它们很少独自一人。设计可视化时,通常会添加文本以为读者提供其他上下文和指导。但是,几乎没有实验证据来指导设计师表明在图表中要显示的文本是什么,其定性属性应该是什么以及应放置在何处。先前的工作还显示了图表与文本表示的个人喜好的变化。在本文中,我们探讨了有关可视化文本组成部分的相对价值的几个研究问题。 302名参与者对包含不同文本数量的单变量线图进行了排名,范围从没有文本(轴除外)到没有视觉效果的书面段落。参与者还描述了他们可以从包含具有不同语义内容的文本的线路图中获取的信息。我们发现大量注释的图表没有受到惩罚。实际上,参与者更喜欢文本注释数量最多的图表,而不是单独的注释或文本较少的图表。我们还发现语义内容的效果。例如,与描述元素或编码组件相比,描述图表的统计或关系组成部分的文本导致更多的要点参考统计或关系比较。最后,我们根据文本在图表上的位置找到了语义级别的不同效果。最好将某些信息放置在标题中,而其他信息应更靠近数据。我们将这些结果汇编为四个图表设计指南,并讨论对文本和图表组合的未来含义。

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.

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