Visualizing Searcher Gaze Patterns

Mustafa Abualsaud, Mark D. Smucker, Charles L. A. Clarke

Abstract: Information retrieval researchers often use eye-tracking to gain insights into searchers' decision making processes. In this paper, we present a visualizing method for summarizing the gaze patterns of multiple searchers on search engine result pages (SERPs). Unlike traditional eye-tracking heat maps, this method includes timing information as part of the visualization, providing additional clarity about searcher fixations as time passes. We demonstrate the visualization technique using eye-tracking data collected as part of a previously published search engine user study and show its value in communicating different patterns of searchers' gaze behavior under different user types and query types. We include a code sample in R to facilitate adoption of the method.