대한인간공학회지 (Journal of the Ergonomics Society of Korea)

  • 제34권5호
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  • Pages.377-399
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  • 2015
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  • 1229-1684(pISSN)
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  • 2093-8462(eISSN)
대한인간공학회 (Ergonomics Society of Korea)
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Mapping Studies on Visual Search, Eye Movement, and Eye track by Bibliometric Analysis

  • Rhie, Ye Lim (Department of Industrial Engineering, Seoul National University) ;
  • Lim, Ji Hyoun (School of Design and Human Engineering, Ulsan National Institute of Science and Technology) ;
  • Yun, Myung Hwan (Department of Industrial Engineering, Seoul National University)
  • 투고 : 2015.04.03
  • 심사 : 2015.05.06
  • 발행 : 2015.10.31
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초록

Objective: The aim of this study is to understand and identify the critical issues in vision research area using content analysis and network analysis. Background: Vision, the most influential factor in information processing, has been studied in a wide range of area. As studies on vision are dispersed across a broad area of research and the number of published researches is ever increasing, a bibliometric analysis towards literature would assist researchers in understanding and identifying critical issues in their research. Method: In this study, content and network analysis were applied on the meta-data of literatures collected using three search keywords: 'visual search', 'eye movement', and 'eye tracking'. Results: Content analysis focuses on extracting meaningful information from the text, deducting seven categories of research area; 'stimuli and task', 'condition', 'measures', 'participants', 'eye movement behavior', 'biological system', and 'cognitive process'. Network analysis extracts relational aspect of research areas, presenting characteristics of sub-groups identified by community detection algorithm. Conclusion: Using these methods, studies on vision were quantitatively analyzed and the results helped understand the overall relation between concepts and keywords. Application: The results of this study suggests that the use of content and network analysis helps identifying not only trends of specific research areas but also the relational aspects of each research issue while minimizing researchers' bias. Moreover, the investigated structural relationship would help identify the interrelated subjects from a macroscopic view.

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