In two-sided marketplaces, items compete for user attention, which translates to revenue for suppliers. Item exposure, indicated by the amount of attention items receive in a ranking, can be influenced by factors like position bias. Recent work suggests that inter-item dependencies, such as outlier items in a ranking, also affect item exposure. Outlier items are items that observably deviate from the other items in a ranked list. Understanding outlier items is crucial for determining an item's exposure distribution. In our previous work, we investigated the impact of different presentational features on users' perception of outlier in search results. In this work, we focus on two key questions left unanswered by our previous work: (i) What is the effect of isolated bottom-up visual factors on item outlierness in product lists? (ii) How do top-down factors influence users' perception of item outlierness in a realistic online shopping scenario? We start with bottom-up factors and employ visual saliency models to evaluate their ability to detect outlier items in product lists purely based on visual attributes. Then, to examine top-down factors, we conduct eye-tracking experiments on an online shopping task. Moreover, we employ eye-tracking to not only be closer to the real-world case but also to address the accuracy problem of reaction time in the visual search task. Our experiments show the ability of visual saliency models to detect bottom-up factors, consistently highlighting areas with strong visual contrasts. The results of our eye-tracking experiment for lists without outliers show that despite being less visually attractive, product descriptions captured attention the fastest, indicating the importance of top-down factors. In our eye-tracking experiments, we observed that outlier items engaged users for longer durations compared to non-outlier items.

翻译：在双边市场中，商品通过争夺用户注意力来为供应商创造收益。商品曝光度（即商品在排序结果中获得注意力的程度）会受到位置偏差等因素的影响。近期研究表明，商品间的相互依赖关系（如排序结果中的异常商品）同样会影响商品曝光。异常商品指在排序列表中可观测到与其他商品存在明显偏差的商品。理解异常商品对于确定商品曝光分布至关重要。在我们先前的研究中，我们探究了不同呈现特征对用户感知搜索结果中异常商品的影响。本研究中，我们聚焦于先前工作尚未解决的两个关键问题：（i）孤立的自底向上视觉因素对商品列表中商品异常性有何影响？（ii）在真实的在线购物场景中，自顶向下因素如何影响用户对商品异常性的感知？我们从自底向上因素入手，采用视觉显著性模型评估其仅基于视觉属性检测商品列表中异常商品的能力。随后，为探究自顶向下因素，我们在在线购物任务中开展眼动追踪实验。此外，采用眼动追踪不仅更贴近现实场景，还能解决视觉搜索任务中反应时间的准确性问题。实验结果表明，视觉显著性模型能够有效检测自底向上因素，持续突出具有强烈视觉对比度的区域。针对无异常商品列表的眼动实验结果显示，尽管商品描述的视觉吸引力较低，但其捕获注意力的速度最快，这揭示了自顶向下因素的重要性。在眼动追踪实验中，我们观察到用户注视异常商品的时间显著长于非异常商品。