Carousels have become the de-facto standard user interface in online services. However, there is a lack of research in carousels, particularly examining how recommender systems may be designed differently than the traditional single-list interfaces. One of the key elements for understanding how to design a system for a particular interface is understanding how users browse. For carousels, users may browse in a number of different ways due to the added complexity of multiple topic defined-lists and swiping to see more items. Eye tracking is the key to understanding user behavior by providing valuable, direct information on how users see and navigate. In this work, we provide the first extensive analysis of the eye tracking behavior in carousel recommenders under the free-browsing setting. To understand how users browse and model their behavior, we examine the following research questions : 1) where do users start browsing, 2) how do users transition from item to item within the same carousel and across carousels, and 3) how does genre preference impact transitions? This work addresses a gap in the field and provides the first extensive empirical results of eye tracked browsing behavior in carousels for improving recommenders. Taking into account the insights learned from the above questions, our final contribution is to provide takeaways for carousel recommender system designers to better optimize their systems for user browsing behavior. The most important being an improved reordering of the ranked item positions to account for browsing behavior after swiping. These contributions aim not only to help improve current systems, but also to encourage and allow the design of new user models, systems, and metrics that are better suited to the complexity of carousel interfaces.

翻译：轮播已成为在线服务中事实上的标准用户界面。然而，目前对轮播界面的研究尚显不足，特别是缺乏关于推荐系统应如何针对轮播界面进行不同于传统单列表界面设计的探讨。理解如何为特定界面设计系统的关键要素之一，在于理解用户的浏览方式。对于轮播界面，由于存在多个按主题定义的列表以及滑动查看更多项目的额外复杂性，用户可能以多种不同方式进行浏览。眼动追踪通过提供关于用户如何观看和导航的宝贵直接信息，是理解用户行为的关键。在本研究中，我们在自由浏览设置下，首次对轮播推荐器中的眼动追踪行为进行了广泛分析。为了理解用户的浏览方式并对其行为建模，我们考察了以下研究问题：1) 用户从何处开始浏览，2) 用户如何在同一个轮播内部以及不同轮播之间进行项目间的转移，3) 类型偏好如何影响转移？本研究填补了该领域的空白，并首次提供了关于轮播界面中眼动追踪浏览行为的广泛实证结果，以改进推荐系统。结合从上述问题中获得的洞察，我们的最终贡献是为轮播推荐系统设计者提供建议，以更好地根据用户浏览行为优化其系统。其中最重要的是改进排序项目位置的重新排列，以考虑滑动后的浏览行为。这些贡献不仅旨在帮助改进现有系统，同时也鼓励并促进行为更适应轮播界面复杂性的新用户模型、系统和指标的设计。