了解在线新闻阅读中的用户注意力和参与度

Dmitry Lagun, M. Lalmas
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引用次数: 97

摘要

先前关于用户与在线媒体互动的研究发现,网页停留时间是反映用户与在线新闻文章互动程度的关键指标。虽然平均而言,停留时间可以合理地估计新闻文章的用户体验,但它无法捕捉用户与页面交互的重要方面,例如用户花多少时间阅读文章与查看其他用户发布的评论,或者用户阅读文章的实际比例。在本文中,我们提出了一组用户粘性类以及新的用户粘性指标,与停留时间不同,这些指标更准确地反映了用户对内容的体验。我们的用户参与度分类提供了清晰且可解释的用户在线新闻参与度分类,并基于用户在页面上花费的时间,用户实际阅读文章的比例以及用户与评论进行交互的数量来定义。此外,我们证明,与停留时间相比,我们的指标相对更容易从新闻文章内容中预测,这使得优化用户参与度更容易实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding User Attention and Engagement in Online News Reading
Prior work on user engagement with online media identified web page dwell time as a key metric reflecting level of user engagement with online news articles. While on average, dwell time gives a reasonable estimate of user experience with a news article, it is not able to capture important aspects of user interaction with the page, such as how much time a user spends reading the article vs. viewing the comment posted by other users, or the actual proportion of article read by the user. In this paper, we propose a set of user engagement classes along with new user engagement metrics that, unlike dwell time, more accurately reflect user experience with the content. Our user engagement classes provide clear and interpretable taxonomy of user engagement with online news, and are defined based on amount of time user spends on the page, proportion of the article user actually reads and the amount of interaction users performs with the comments. Moreover, we demonstrate that our metrics are relatively easier to predict from the news article content, compared to the dwell time, making optimization of user engagement more attainable goal.
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