Modeling Sub-Document Attention Using Viewport Time
Modeling Sub-Document Attention Using Viewport Time
复制标题
使用视口时间建模子文档注意力
DOI：
10.1145/3025453.3025916
复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
Mor Naaman
中科院分区：
文献类型：
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作者：
Max Grusky;J. Jahani;Josh Schwartz;D. Valente;Yoav Artzi;Mor Naaman
来自数百万用户（例如页面滚动和视口位置）所捕获的网站参与度度量可以通过使用更简单的措施（例如停留时间）提供对注意力的深入了解。使用来自120万新闻阅读会话的数据，我们检查并评估了从视口时间计算出的三个越来越复杂的子档案记录的模型，即在用户显示上可见页面组件的时间。我们的建模结合了有关屏幕上读取的事先注视知识，并通过显示用于估计用户阅读率时如何与已知的经验措施相吻合来验证它。然后，我们展示我们的模型如何揭示文章主题与对页面元素的关注之间的相互作用。我们的方法支持精致的大规模测量用户参与度，仅在基于实验室的眼睛跟踪研究中获得的水平。
Website measures of engagement captured from millions of users, such as in-page scrolling and viewport position, can provide deeper understanding of attention than possible with simpler measures, such as dwell time. Using data from 1.2M news reading sessions, we examine and evaluate three increasingly sophisticated models of sub-document attention computed from viewport time, the time a page component is visible on the user display. Our modeling incorporates prior eye-tracking knowledge about onscreen reading, and we validate it by showing how, when used to estimate user reading rate, it aligns with known empirical measures. We then show how our models reveal an interaction between article topic and attention to page elements. Our approach supports refined large-scale measurement of user engagement at a level previously available only from lab-based eye-tracking studies.