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eyeScrollR: A software method for reproducible mapping of eye tracking data from scrollable web pages
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The 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 to scroll web pages. We describe the R package eyeScrollR for mapping eye-tracking data to scroll content such as web pages. The package re-maps eye-tracking gaze coordinates to web 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 validity of the package by triangulating it with manual coding and commercial software (iMotions). We find the highest agreement between the eyeScrollR package and manual coding. Because it arbitrarily modifies two-thirds of the fixations, the iMotions software has the lowest agreement with the other methods. Compared to current methods, eyeScrollR provides a more reproducible and reliable approach for mapping eye-tracking data to scroll web pages. With its open code and free availability, we recommend eyeScrollR as an essential tool for eyetracking 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.
Title: eyeScrollR: A software method for reproducible mapping of eye tracking data from scrollable web pages
Description:
The 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 to scroll web pages.
We describe the R package eyeScrollR for mapping eye-tracking data to scroll content such as web pages.
The package re-maps eye-tracking gaze coordinates to web 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 validity of the package by triangulating it with manual coding and commercial software (iMotions).
We find the highest agreement between the eyeScrollR package and manual coding.
Because it arbitrarily modifies two-thirds of the fixations, the iMotions software has the lowest agreement with the other methods.
Compared to current methods, eyeScrollR provides a more reproducible and reliable approach for mapping eye-tracking data to scroll web pages.
With its open code and free availability, we recommend eyeScrollR as an essential tool for eyetracking 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.
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