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Title:Understanding the effectiveness of visual cues through analyzing eye gaze data
Author(s):Zhu, Wenjie
Advisor(s):Karahalios, Karrie
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Visual cues
narrative visualization
Eye tracking
Abstract:Historically eye movement analysis has been viewed to provide a window onto the audience’s mind, as stated in the eye mind hypothesis and it has been found that eye gaze pattern and mental process is closely related. To investigate the effectiveness of visual cues accompanied by audio narration, we performed an in-lab eye-tracking study. By interpreting eye gaze data using several eye gaze metrics for collective eye movement analysis along with visualizations of eye gaze plots, we examined how each of the eye gaze metrics reveals the effects of the visual cues and how the content of visualizations is processed by people's eyes. Specifically, we found that some of the visual cues help guide the audience's attention to form a more clustered eye gaze pattern (i.e., the brightness cue for the graduate arrow plot), and also some of the visual cues outperform in guiding the audience into simplified eye gaze transition paths relative to other cues (i.e., the glow cue is more capable than shape cue, arrow cue, and depth of field cue for the SNS heatmap). Besides, the eye gaze pattern varies based on different properties of the visualization (e.g., the middle class slope graphs produce a less clustered gaze pattern overall). This thesis makes contributions to provide presenters implications regarding factors to consider when choosing visual cues (i.e., the property of each cue, the property of the selected visual element relative to the chart, etc) and provide insights of choosing eye gaze metrics for future researchers.
Issue Date:2019-07-17
Type:Thesis
URI:http://hdl.handle.net/2142/105956
Rights Information:Copyright 2019 Wenjie Zhu
Date Available in IDEALS:2019-11-26
Date Deposited:2019-08


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