Words of Estimative Correlation: Studying Verbalizations of Scatterplots.
Words of Estimative Correlation: Studying Verbalizations of Scatterplots.
复制标题
估计相关性的词语：研究散点图的语言化。
DOI：
10.1109/tvcg.2020.3023537
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发表时间：
2022
影响因子：
5.2
通讯作者：
Henkin R
中科院分区：
文献类型：
--
作者：
Henkin R
自然语言和可视化越来越多地被部署在一起，以不同的方式支持数据分析，从多模式交互到丰富的数据摘要和见解。然而，研究人员仍然缺乏系统的知识，观众如何用言语表达他们的视觉化的解释，以及他们如何在这样的背景下解释视觉化的言语化。我们描述了两项研究，旨在确定这些任务中相关的数据和图表的特征。第一项研究要求参与者用语言描述他们在散点图中看到的东西，这些散点图描绘了各种程度的相关性。第二项研究要求参与者选择与给定的相关性口头描述相匹配的可视化。我们从响应中提取关键概念，将它们组织在分类中并分析分类的响应。我们观察到，参与者在所有散点图中使用广泛的词汇，但特定的概念更倾向于更高水平的相关性。对这些研究进行比较后发现，其中一些概念存在歧义。我们讨论了这些结果如何为与数据和分析任务相一致的多模态表示的设计提供信息，并提出了一个研究路线图，以加深对可视化和自然语言的理解。
Natural language and visualization are being increasingly deployed together for supporting data analysis in different ways, from multimodal interaction to enriched data summaries and insights. Yet, researchers still lack systematic knowledge on how viewers verbalize their interpretations of visualizations, and how they interpret verbalizations of visualizations in such contexts. We describe two studies aimed at identifying characteristics of data and charts that are relevant in such tasks. The first study asks participants to verbalize what they see in scatterplots that depict various levels of correlations. The second study then asks participants to choose visualizations that match a given verbal description of correlation. We extract key concepts from responses, organize them in a taxonomy and analyze the categorized responses. We observe that participants use a wide range of vocabulary across all scatterplots, but particular concepts are preferred for higher levels of correlation. A comparison between the studies reveals the ambiguity of some of the concepts. We discuss how the results could inform the design of multimodal representations aligned with the data and analytical tasks, and present a research roadmap to deepen the understanding about visualizations and natural language.