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Contribution Details
| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Identifying Reading Patterns with Eye-tracking Visual Analytics |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
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| ISBN | 9781450371353 |
| Page Range | 1 - 3 |
| Event Title | ETRA '20: 2020 Symposium on Eye Tracking Research and Applications |
| Event Type | conference |
| Event Location | Stuttgart Germany |
| Event Start Date | July 2 - 2020 |
| Event End Date | July 5 - 2020 |
| Place of Publication | New York, NY, USA |
| Publisher | ACM |
| Abstract Text | Eye-tracking studies can yield insight into patterns of reading strategies, but identifying patterns in eye-tracking visualizations is a cognitively demanding task. My dissertation explores how visual analytics approaches support analysts detecting sequential patterns in the eye tracking data. To demonstrate the effectiveness of our visual analytics, I apply it to the datasets from a series of eye-tracking studies, and gather an empirical understanding about how research articles are read on paper and other media. |
| Digital Object Identifier | 10.1145/3379157.3391994 |
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