Gaze analysis of user characteristics in magazine style narrative visualizations
Gaze analysis of user characteristics in magazine style narrative visualizations
复制标题
杂志风格叙事可视化中用户特征的注视分析
DOI：
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发表时间：
2019
影响因子：
3.6
通讯作者：
G. Carenini
中科院分区：
文献类型：
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作者：
Dereck Toker;C. Conati;G. Carenini
先前的研究表明，各种用户特征（例如认知能力、个性特征和学习能力）可以影响信息可视化任务中的用户体验。这些发现促使研究人员研究用户自适应信息可视化，这些可视化可以根据用户的特定需求提供个性化支持来帮助用户。虽然现有的工作大多仅限于仅涉及可视化的任务，但我们研究的目的是扩大这项工作，以包括用户使用嵌入式可视化处理文本文档的场景，即杂志风格叙事可视化，简称 MSNV。在本文中，我们分析了通过 MSNV 进行的用户研究中收集的眼动追踪数据，以揭示对这些用户特征能力较低的用户的用户体验（即任务时间）产生负面影响的处理行为。我们的分析利用线性混合效应模型来评估用户特征、注视处理行为和任务绩效之间的关系。我们的结果确定了可视化中的几种 MSNV 处理行为，这些行为会导致阅读能力较低的用户的任务性能较差。例如，我们发现，与其他用户相比，阅读能力较低的用户在相关条形图和不相关条形图之间转换的频率明显更高，并且更频繁地从条形图转换到标签。我们将我们的发现作为设计用户自适应支持机制的一步，以缓解 MSNV 的这些困难，并就如何利用我们的结果为未来评估创建一组有意义的干预措施提供建议（例如，在可视化中动态突出显示相关条形和标签，以帮助阅读能力较低的用户更有效地找到它们）。
Previous research has shown that various user characteristics (e.g., cognitive abilities, personality traits, and learning abilities) can influence user experience during information visualization tasks. These findings have prompted researchers to investigate user-adaptive information visualizations that can help users by providing personalized support based on their specific needs. Whereas existing work has been mostly limited to tasks involving just visualizations, the aim of our research is to broaden this work to include scenarios where users process textual documents with embedded visualizations, i.e., Magazine Style Narrative Visualizations, or MSNVs for short. In this paper, we analyze eye tracking data collected from a user study with MSNVs to uncover processing behaviors that are negatively impacting user experience (i.e., time on task) for users with low abilities in these user characteristics. Our analysis leverages Linear Mixed-Effects Models to evaluate the relationships among user characteristics, gaze processing behaviors, and task performance. Our results identify several MSNV processing behaviors within the visualization that contribute to poor task performance for users with low reading proficiency. For instance, we identify that users with low reading proficiency transition significantly more often compared to their counterparts between relevant and non-relevant bars, and transition more often from bars to the labels. We present our findings as a step toward designing user-adaptive support mechanisms to alleviate these difficulties with MSNVs, and provide suggestions on how our results can be leveraged for creating a set of meaningful interventions for future evaluation (e.g., dynamically highlighting relevant bars and labels in the visualization to help users with low reading proficiency locate them more effectively).