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Similarities and Differences Between Eye and Mouse Dynamics During Web Pages Exploration.

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Researchers explored the link between eye, mouse, and scroll movements during web browsing. They found distinct patterns in movement and fixation, showing eye and mouse actions align, while scrolling acts oppositely.

Keywords:
behaviorcomputer mouseeye movementscrollweb page

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Area of Science:

  • Human-Computer Interaction
  • Behavioral Analysis
  • Web Usability

Background:

  • Eye movements are crucial for understanding human behavior but eye-tracking is difficult to scale and expensive.
  • Web browsing behavior analysis is limited by the inaccessibility of traditional eye-tracking methods.
  • The relationship between eye movements and computer mouse interactions offers a scalable alternative for behavioral analysis.

Purpose of the Study:

  • To investigate the link between eye, mouse, and scroll movements during web browsing.
  • To develop new analysis methods for characterizing the eye-mouse-scroll relationship.
  • To determine if this relationship is task-dependent or exhibits consistent patterns.

Main Methods:

  • Recorded eye, mouse, and scroll movements of 151 participants across 18 dynamic web pages.
  • Participants performed free viewing and visual search tasks for 20 seconds each.
  • Analyzed temporal changes and patterns in movement and fixation parameters.

Main Results:

  • Significant temporal differences were observed in eye, mouse, and scroll parameters, stabilizing by the end of exploration.
  • Two distinct patterns emerged: one for movement parameters and another for dwelling/fixation parameters.
  • Eye and mouse movements showed consistency within their pattern, while scrolling exhibited an inverse relationship.

Conclusions:

  • A task-independent relationship exists between eye, mouse, and scroll parameters during web browsing.
  • The findings suggest distinct but related mechanisms govern movement and fixation behaviors.
  • This research provides a foundation for scalable, non-invasive analysis of web user behavior.