Applying computational tools to predict gaze direction in interactive visual environments
ACM Transactions on Applied Perception (TAP)
An experimental comparison of click position-bias models
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
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The task of selecting one among several items in a visual display is extremely common in daily life and is executed billions of times every day on the Web. Attention is vital for selection, but the end-to-end process of what draws and sustains attention, and how that influences selection, remains poorly understood. We study this in a complex multi-item selection setting, where participants selected one among eight news articles presented in a grid layout on a screen. By varying the position, saliency, and topic of the news items, we identify the relative importance of these visual and semantic factors in attention and selection. We present a simple model of attention that predicts many key features such as attention shifts and dwell time per item. Potential applications of our findings include optimizing visual displays to drive user attention.