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Intelligent Mapping of Eye-Tracking Gaze-Data on Fixed Web Page Elements

  • The output of eye tracking Web usability studies can be visualized to the analysts as screenshots of the Web pages with their gaze data. However, the screenshot visualizations are found to be corrupted whenever there are recorded fixations on fixed Web page elements on different scroll positions. The gaze data are not gathered on their fixated fixed elements; rather they are scattered on their recorded scroll positions. This problem has raised our attention to find an approach to link gaze data to their intended fixed elements and gather them in one position on the screenshot. The approach builds upon the concept of creating the screenshot during the recording session, where images of the viewport are captured on visited scroll positions and lastly stitched into one Web page screenshot. Additionally, the fixed elements in the Web page are identified and linked to their fixations. For the evaluation, we compared the interpretation of our enhanced screenshot against the video visualization, which overcomes the problem. The results revealed that both visualizations equally deliver accurate interpretations. However, interpreting the visualizations of eye tracking Web usability studies using the enhanced screenshots outperforms the video visualizations in terms of speed and it requires less temporal demands from the interpreters.

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Author:Hanadi Tamimi
URN:urn:nbn:de:kola-15470
Referee:Steffen Staab
Advisor:Raphael Menges
Document Type:Master's Thesis
Language:English
Date of completion:2017/12/14
Date of publication:2017/12/15
Publishing institution:Universität Koblenz-Landau, Universitätsbibliothek
Granting institution:Universität Koblenz-Landau, Campus Koblenz, Fachbereich 4
Date of final exam:2017/12/19
Release Date:2017/12/15
Number of pages:ix, 50
Institutes:Fachbereich 4 / Institute for Web Science and Technologies
Licence (German):License LogoEs gilt das deutsche Urheberrecht: § 53 UrhG