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

Nathanael Larigaldie¹, Anna Dreneva², Jacob L Orquin^2,3

¹Aarhus University, Aarhus C, Denmark. larigaldie.n@mgmt.au.dk.

Behavior Research Methods

|February 12, 2024

Summary

This summary is machine-generated.

Researchers can now accurately map eye-tracking data from scrollable web pages using the new R package, eyeScrollR. This tool enhances the reliability and reproducibility of online attention studies.

Keywords:

Eye tracking Gaze mapping Open source Scrollable web pages Software

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Area of Science:

Human-Computer Interaction
Cognitive Psychology
Usability Research

Background:

The internet is integral to modern life, driving increased use of eye-tracking technology to study online behavior.
Mapping eye-tracking data from dynamic, scrollable web pages presents a significant methodological challenge for researchers.
Existing methods lack the precision and standardization required for analyzing attention on web content.

Purpose of the Study:

To introduce eyeScrollR, an R package designed to accurately map eye-tracking data from scrollable web pages.
To provide a reproducible and reliable solution for researchers studying online attention and behavior.
To facilitate standardized analysis of eye-tracking data within web scrolling contexts.

Main Methods:

Development of the eyeScrollR R package utilizing a deterministic algorithm.
Re-mapping of eye-tracking gaze coordinates to full-page coordinates using mouse scroll data.
Incorporation of features to handle elements like sticky menus and persistent ads during scrolling.
Validation through testing across diverse hardware, software, and web page configurations.

Main Results:

The eyeScrollR package demonstrates high accuracy in mapping eye-tracking data when compared to manual coding.
The package effectively handles common web page complexities, ensuring robust data mapping.
Validation confirms the package's reliability across various testing environments.

Conclusions:

eyeScrollR offers a reproducible and reliable method for mapping eye-tracking data from scrollable web pages.
The package is a valuable, open-source tool for eye-tracking researchers, especially those committed to open science.
eyeScrollR enhances the analysis of user attention and behavior in complex online environments.