نوع مقاله : مقاله پژوهشی

نویسندگان

1 PhD Student in Human Resources and Organizational Behavior, Yazd University

2 Associate Professor Allameh Tabatabaei University, Faculty of Psychology and Education

3 Phd Student in Educational Psychology, Allameh Tabatabaei University, Faculty of Psychology

چکیده

Introduction and Objective: Eye-tracking has emerged as a powerful tool in psychology, education, and technology, and understanding its global research trends is essential for mapping its scholarly evolution. This study aims to explore the global trends and developmental trajectory of Eye Tracking research by employing a scient metric analysis to offer a holistic overview of its scholarly growth and impact.
Research Methodology: A systematic search was conducted in the Web of Science database, retrieving 4,370 relevant articles published between 1990 and 2021. The data were analyzed using VOS viewer software through co-authorship networks, keyword co-occurrence mapping, and trend visualization techniques. Findings: The results reveal a significant and accelerating growth in Eye Tracking publications, particularly over the past decade. Prominent keywords such as Eye-tracking, Movements, Information, Attention, Perception, Children, and Performance reflect the field's thematic diversity and growing relevance across various disciplines. A notable shift in research focus is observed—from early investigations into psychological disorders to more recent emphasis on cognitive processes and executive functions.
Conclusion: This study provides a comprehensive roadmap of the evolution of Eye Tracking research, offering valuable insights into past trends, present hotspots, and future directions, with implications for its application in domains such as education, marketing, and technology.
Value: The novelty of this research lies in its integrative use of scient metric tools to identify emerging topics, map interdisciplinary connections, and highlight underexplored areas in Eye Tracking studies.

کلیدواژه‌ها

عنوان مقاله [English]

Global Trends and Evolution in Eye Tracking Research: A Scientometric Analysis Using VOS Viewer

نویسندگان [English]

  • Mahshid Pourhosein 1
  • Soqra Ebrahimighavam 2
  • Mehdi Aslanzadeh 2
  • Majid Firouzkouhi berenj abadi 3

1 PhD Student in Human Resources and Organizational Behavior, Yazd University

2 Associate Professor Allameh Tabatabaei University, Faculty of Psychology and Education

3 Phd Student in Educational Psychology, Allameh Tabatabaei University, Faculty of Psychology

چکیده [English]

Introduction and Objective: Eye-tracking has emerged as a powerful tool in psychology, education, and technology, and understanding its global research trends is essential for mapping its scholarly evolution. This study aims to explore the global trends and developmental trajectory of Eye Tracking research by employing a scient metric analysis to offer a holistic overview of its scholarly growth and impact.
Research Methodology: A systematic search was conducted in the Web of Science database, retrieving 4,370 relevant articles published between 1990 and 2021. The data were analyzed using VOS viewer software through co-authorship networks, keyword co-occurrence mapping, and trend visualization techniques. Findings: The results reveal a significant and accelerating growth in Eye Tracking publications, particularly over the past decade. Prominent keywords such as Eye-tracking, Movements, Information, Attention, Perception, Children, and Performance reflect the field's thematic diversity and growing relevance across various disciplines. A notable shift in research focus is observed—from early investigations into psychological disorders to more recent emphasis on cognitive processes and executive functions.
Conclusion: This study provides a comprehensive roadmap of the evolution of Eye Tracking research, offering valuable insights into past trends, present hotspots, and future directions, with implications for its application in domains such as education, marketing, and technology.
Value: The novelty of this research lies in its integrative use of scient metric tools to identify emerging topics, map interdisciplinary connections, and highlight underexplored areas in Eye Tracking studies.

کلیدواژه‌ها [English]

  • Eye Tracking Research
  • Scientometric
  • Analysis
  • VOS Viewer
  • Web of Science

Reference

Allopenna, P. D., Magnuson, J. S., & Tanenhaus, M. K. (1998). Tracking the time course of spoken word recognition using eye movements: Evidence for continuous mapping models. Journal of memory and language, 38(4), 419-439. https://doi.org/10.1006/jmla.1997.2558
Anderson, John R. (2015). Cognitive Psychology and Its Implications. Eighth edition. New York: Worth Publishers.
Aria, M., & Cuccurullo, C. (2017). bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975. https://doi.org/10.1016/j.joi.2017.08.007
Armstrong, T., & Olatunji, B. O. (2012). Eye tracking of attention in the affective disorders: A meta-analytic review and synthesis. Clinical psychology review, 32(8), 704-723. https://doi.org/10.1016/j.cpr.2012.09.004.
Blignaut, P. (2018). The Effect of Real-time Headbox Adjustments on Data Quality. Journal of Eye Movement Research11(1). https://doi.org/10.16910/jemr.11.1.4
Bornmann, L., & Daniel, H. D. (2007). What do we know about the h index? Journal of the American Society for Information Science and Technology, 58(9), 1381–1385. https://doi.org/10.1002/asi.20609
Carter, B. T., & Luke, S. G. (2020). Best practices in eye tracking research. International Journal of Psychophysiology, 155, 49-62. https://doi.org/10.1016/j.ijpsycho.2020.05.010
Chen, X., Jiang, M., & Zhao, Q. (2024, September). Gazexplain: Learning to predict natural language explanations of visual scanpaths. In European Conference on Computer Vision (pp. 314-333). Cham: Springer Nature Switzerland. https://arxiv.org/abs/2408.02788
Chen, Z., Fu, H., Lo, W. L., & Chi, Z. (2018). Strabismus recognition using eye-tracking data and convolutional neural networks. Journal of healthcare engineering, 2018. https://doi.org/10.1155/2018/7692198
Clay, V., König, P., & Koenig, S. (2019). Eye tracking in virtual reality. Journal of eye movement research, 12(1), 10-16910. https://doi.org/10.16910/jemr.12.1.3.
Colliot, T., & Jamet, É. (2018). Understanding the effects of a teacher video on learning from a multimedia document: an eye-tracking study. Educational Technology Research and Development, 66(6), 1415-1433. https://doi.org/10.1007/s11423-018-9594-x.
Cornelissen, F. W., Peters, E. M., & Palmer, J. (2002). The Eyelink Toolbox: eye tracking with MATLAB and the Psychophysics Toolbox. Behavior Research Methods, Instruments, & Computers, 34(4), 613-617. https://doi.org/10.3758/BF03195489
Cutumisu, M., Turgeon, K. L., Saiyera, T., Chuong, S., González Esparza, L. M., MacDonald, R., & Kokhan, V. (2019). Eye tracking the feedback assigned to undergraduate students in a digital assessment game. Frontiers in psychology, 10, 1931. https://doi.org/10.3389/fpsyg.2019.01931
De Cock, P., Hermens, F., Verplaetse, K., Vandekerckhove, M., & Van Waes, L. (2019). Eye tracking and cognitive processing: A methodological guide for mapping cognitive strategies. Behavior Research Methods, 51(3), 1239–1255. https://doi.org/10.3758/s13428-018-1132-8
Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296. https://doi.org/10.1016/j.jbusres.2021.04.070
Duchowski, A. T. (2002). A breadth-first survey of eye-tracking applications. Behavior Research Methods, Instruments, & Computers, 34(4), 455-470. https://doi.org/10.3758/BF03195475.
Elbaum, T., Eizenman, M., & Yang, X. (2017). Advances in infrared eye tracking technology: Implications for vision research. Vision Research, 134, 58–66. https://doi.org/10.1016/j.visres.2017.03.003
Eraslan, S., Yesilada, Y., & Harper, S. (2015). Eye tracking scanpath analysis techniques on web pages: A survey, evaluation and comparison. Journal of Eye Movement Research9(1). https://doi.org/10.16910/jemr.9.1.2
Esmaeili Mahyari, M., Irani, H. R. and noormandi pour, V. (2021). Biblometric Review on Smart Tourism Researches. Tourism and Leisure Time, 6(12), 21-35. https://doi.org/10.22133/tlj.2022.332168.1031
Gegenfurtner, A., Lehtinen, E., & Säljö, R. (2011). Expertise differences in the comprehension of visualizations: A meta-analysis of eye-tracking research in professional domains. Educational psychology review, 23, 523-552. https://doi.org/10.1007/s10648-011-9174-7.
Grüner, M., & Ansorge, U. (2017). Mobile eye tracking during real-world night driving: A selective review of findings and recommendations for future research. Journal of Eye Movement Research10(2). https://doi.org/10.16910/jemr.10.2.1
Hang, Y., Yi, X., & Xianglan, C. (2018). Eye-tracking studies in visual marketing: Review and prospects. Foreign Economics & Management, 40(12), 98-108. https://doi.org/10.16538/j.cnki.fem.2018.12.007.
Hasse, A., & Bruder, C. (2023). Eye tracking, usability, and user experience: A systematic review. International Journal of Human–Computer Interaction, 39(10), 1–18. https://doi.org/10.1080/10447318.2023.2221600
Hassoumi, A., Tena, A., & Ruiz-Romero, J. (2018). Cognitive load measurement using eye tracking in e-learning environments. International Journal of Human–Computer Interaction, 34(10), 930–941. https://doi.org/10.1080/10447318.2018.1471579
Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences, 102(46), 16569–16572. https://doi.org/10.1073/pnas.0507655102
Holzinger, A. (2014). Biomedical informatics: discovering knowledge in big data. Springer.
Holzman, P. S., Proctor, L. R., & Hughes, D. W. (1973). Eye-tracking patterns in schizophrenia. Science, 181(4095), 179-181. https://doi.org/10.1126/science.181.4095.179.
Holzman, P. S., Proctor, L. R., Levy, D. L., Yasillo, N. J., Meltzer, H. Y., & Hurt, S. W. (1974). Eye-tracking dysfunctions in schizophrenic patients and their relatives. Archives of general psychiatry, 31(2), 143-151. https://doi.org/10.1001/archpsyc.1974.01760140005001
Horsley, M., Eliot, M., Knight, B. A., & Reilly, R. (Eds.). (2013). Current trends in eye tracking research. Springer Science & Business Media.
Ivanchenko, S., Nurmagambetov, T., & Gorbunov, R. (2021). Eye tracking and attention mapping: From laboratory to real-world applications. Frontiers in Psychology, 12, 645–658. https://doi.org/10.3389/fpsyg.2021.645858
Kays, R., Crofoot, M. C., Jetz, W., & Wikelski, M. (2015). Terrestrial animal tracking as an eye on life and planet. Science, 348(6240), aaa2478. https://doi.org/10.1126/science.aaa2478.
Klaib, A. F., Alsrehin, N. O., Melhem, W. Y., Bashtawi, H. O., & Magableh, A. A. (2021). Eye tracking algorithms, techniques, tools, and applications with an emphasis on machine learning and Internet of Things technologies. Expert Systems with Applications, 166, 114037. https://doi.org/10.1016/j.eswa.2020.114037
Li, M., & Zhao, Y. (2022). Mapping collaboration networks and thematic trends in third language acquisition research: A bibliometric analysis based on Scopus. Frontiers in Psychology, 13, 1021517. https://doi.org/10.3389/fpsyg.2022.1021517
Lukander, K. (2016). A short review and primer on eye tracking in human computer interaction applications. arXiv preprint arXiv:1609.07342. https://doi.org/10.48550/arXiv.1609.07342
Morimoto, C. H., & Mimica, M. R. (2005). Eye gaze tracking techniques for interactive applications. Computer vision and image understanding, 98(1), 4-24. https://doi.org/10.1016/j.cviu.2004.07.010.
Obaidellah, U., Al Haek, M., & Cheng, P. C. H. (2018). A survey on the usage of eye-tracking in computer programming. ACM Computing Surveys (CSUR), 51(1), 1-58. https://doi.org/10.1145/3145904
Park, S. J., Subramaniyam, M., Hong, S., Kim, D., & Yu, J. (2017). Conceptual design of the elderly healthcare services in-vehicle using IoT. WCX™ 17: SAE World Congress Experience. Detroit.
Perianes-Rodriguez, A., Waltman, L., & Van Eck, N. J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178–1195. https://doi.org/10.1016/j.joi.2016.10.006
Rainoldi, M., & Jooss, C. (2020). Eye-tracking in UX research: A review and practical guide. International Journal of Human–Computer Studies, 141, 102439. https://doi.org/10.1016/j.ijhcs.2020.102439
Rashbass, C. (1961). The relationship between saccadic and smooth tracking eye movements. The Journal of physiology, 159(2), 326. https://doi.org/10.1113/jphysiol.1961.sp006811
Rigas, I., Friedman, L., & Komogortsev, O. (2018). Study of an Extensive Set of Eye Movement Features: Extraction Methods and Statistical Analysis. Journal of Eye Movement Research11(1). https://doi.org/10.16910/jemr.11.1.3
Sharafi, Z., Soh, Z., & Guéhéneuc, Y. G. (2015). A systematic literature review on the usage of eye-tracking in software engineering. Information and Software Technology, 67, 79-107. https://doi.org/10.1016/j.infsof.2015.06.008
Strukelj, A., & Niehorster, D. C. (2018). One page of text: Eye movements during regular and thorough reading, skimming, and spell checking. Journal of Eye Movement Research11(1). https://doi.org/10.16910/jemr.11.1.1
Toivanen, M., Lukander, K., & Puolamäki, K. (2017). Probabilistic approach to robust wearable gaze tracking. Journal of Eye Movement Research10(4). https://doi.org/10.16910/jemr.10.4.2
Ulutas, B. H., Özkan, N. F., & Michalski, R. (2020). Application of hidden Markov models to eye tracking data analysis of visual quality inspection operations. Central European Journal of Operations Research, 28, 761–777. https://doi.org/10.1007/s10100-019-00628-x.
van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538. https://doi.org/10.1007/s11192-009-0146-3
Verma, R., Lobos, V., Merig´o, J. M., Cancino, C., & Sienz, J. (2020). Forty years of Applied Mathematical Modelling: A bibliometric study. Applied Mathematical Modelling, 89(2), 1177–1197. https://doi.org/10.1016/j.apm.2020.07.004.
Waltman, L., Kaltenbrunner, W., Pinfield, S., & Woods, H. B. (2023). How to improve scientific peer review: Four schools of thought. Learned Publishing, 36(3), 334-347. https://doi.org/10.1002/leap.1544.
Zancanaro, A., Todesco, J. L., & Ramos, F. (2015). A bibliometric mapping of open educational resources. International Review of Research in Open and Distributed Learning, 16(1), 1-23. https://doi.org/10.1007/s10100-019-00628-x