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Mapping Eye-Tracking Research in Human-Computer Interaction: A Science-Mapping and Content-Analysis Study
1Department of Computer Technologies, Gönen Vocational School, Bandırma Onyedi Eylül University, Bandırma 10200, Türkiye.
Eye tracking is revolutionizing human-computer interaction (HCI), moving beyond measurement to enable interaction design, cognitive assessment, and accessibility. This review maps key research trends and future directions in HCI eye-tracking studies.
Area of Science:
- Human-Computer Interaction (HCI)
- Computer Science
- Cognitive Science
Background:
- Eye tracking is a key method in HCI, driven by AI and sensing tech advancements.
- A comprehensive overview of eye-tracking research in HCI is needed.
- This study analyzes 1033 publications from 2020-2025.
Purpose of the Study:
- To provide a bibliometric and content analysis of eye-tracking research in HCI.
- To identify dominant research themes and trends.
- To outline future research directions and identify gaps.
Main Methods:
- Bibliometric network analysis of 1033 publications from Web of Science and Scopus.
- Keyword co-occurrence, co-citation, co-authorship, and source mapping using VOSviewer.
- Qualitative content analysis of the 50 most-cited papers.
Main Results:
- Four main research axes identified: deep-learning gaze estimation, XR interactions, cognitive load/human factors, and usability/accessibility.
- Most-cited studies focus on immersive gaze interaction, deep learning, multimodal interaction, and cognitive load.
- Research teams are typically small- to medium-sized.
Conclusions:
- Eye tracking in HCI is shifting from a measurement tool to an enabling technology for interaction, cognition, and accessibility.
- Future directions include benchmarking, real-world applications, and privacy-preserving analytics.
- Ethical considerations, particularly privacy, are increasingly important.
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