eyeScrollR: A software method for reproducible mapping of eye-tracking data from scrollable web pages

Abstract

AbstractThe Internet has become an important part of our lives and an increasing number of researchers use eye-tracking technology to examine attention and behavior in online environments. Researchers, however, face a significant challenge in mapping eye-tracking data from scrollable web pages. We describe the R package eyeScrollR for mapping eye-tracking data from scrollable content such as web pages. The package re-maps eye-tracking gaze coordinates to full-page coordinates with a deterministic algorithm based on mouse scroll data. The package includes options for handling common situations, such as sticky menus or ads that remain visible when the user scrolls. We test the package’s validity in different hardware and software settings and on different web pages and show that it is highly accurate when tested against manual coding. Compared to current methods, eyeScrollR provides a more reproducible and reliable approach for mapping eye-tracking data from scrollable web pages. With its open code and free availability, we recommend eyeScrollR as an essential tool for eye-tracking researchers, particularly those who adhere to open-science principles. The eyeScrollR package offers a valuable contribution to the field of eye-tracking research, facilitating accurate and standardized analysis of eye-tracking data in web scrolling contexts.