Riding the Carousel: The First Extensive Eye Tracking Analysis of Browsing Behavior in Carousel Recommenders
Santiago de Leon-Martinez, Robert Moro, Branislav Kveton, Maria Bielikova

TL;DR
This paper presents the first extensive eye tracking analysis of user browsing behavior in carousel recommender interfaces, providing insights to optimize system design for better user engagement.
Contribution
It offers novel empirical insights into eye movement patterns in carousels and proposes design takeaways to improve recommender system performance based on user browsing behavior.
Findings
Users often start browsing from the top of carousels.
Transitions within and across carousels are influenced by genre preferences.
Reordering item positions can enhance browsing efficiency.
Abstract
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…
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