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Gaze Analysis on the Effect of Intervention on Ruminative Web Browsing

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Advances in Artificial Intelligence (JSAI 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1423))

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Abstract

In the current highly developed information society, having a habit of rumination (repetitive and negative thinking) can be dangerous to our mental health. To prevent rumination during web browsing, the authors’ previous study built an advertisement system that is regulated by a computational cognitive model and users’ heart rate variability (HRV). To validate and extend the system, this paper presents analyses of behavioral and physiological data obtained from two studies where participants engaged in two successive tasks: mood induction and main tasks. Study 1 aimed to develop a detector for rumination distraction utilizing behavioral and physiological data. Owing to the SVM classification, a large contribution of gaze extracted from the facial movie was verified. To validate these findings, Study 2, in which a small number of participants engaged in the same tasks as Study 1, was conducted with a well-established eye-tracking system. Analyses of the gaze data obtained with this device confirmed high consistency with the data obtained from the facial movies, and also confirmed the influence of advertisements on participants’ attention during web browsing. Summarizing the results of these studies, the current paper indicates the validity of distracting rumination by presenting prompts regulated with a personalized cognitive model.

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Notes

  1. 1.

    We developed a browser extension to collect images on the browser when the user visits specific shopping sites (Amazon and Rakuten).

References

  1. Anderson, J.R., Schooler, L.J.: Reflections of the environment in memory. Psychol. Sci. 2(6), 396–408 (1991)

    Article  Google Scholar 

  2. Anderson, J.R.: How Can the Human Mind Occur in the Physical Universe? Oxford University Press, Oxford (2007)

    Book  Google Scholar 

  3. Baltrusaitis, T., Zadeh, A., Lim, Y.C., Morency, L.P.: OpenFace 2.0: facial behavior analysis toolkit. In: 2018 13th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2018), pp. 59–66. IEEE (2018)

    Google Scholar 

  4. Calabrese, B., Cannataro, M.: Sentiment analysis and affective computing: methods and applications. In: Amunts, K., Grandinetti, L., Lippert, T., Petkov, N. (eds.) Brain-Inspired Computing, vol. 10087, pp. 169–178. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-50862-7_13

    Chapter  Google Scholar 

  5. Dancy, C.L., Ritter, F.E., Berry, K.A., Klein, L.C.: Using a cognitive architecture with a physiological substrate to represent effects of a psychological stressor on cognition. Comput. Math. Organ. Theor. 21(1), 90–114 (2014). https://doi.org/10.1007/s10588-014-9178-1

    Article  Google Scholar 

  6. He, H., et al.: Real-time eye-gaze based interaction for human intention prediction and emotion analysis. In: Proceedings of Computer Graphics International 2018, pp. 185–194 (2018)

    Google Scholar 

  7. Itabashi, K., Morita, J., Hirayama, T., Mase, K., Yamada, K.: Interactive model-based reminiscence using a cognitive model and physiological indices. In: Proceedings of the 19th International Conference on Cognitive Modeling, pp. 93–99. Pennsylvania State University, USA (2020)

    Google Scholar 

  8. Morita, J., Pitakchokchai, T., Raj, G.B., Yamamoto, Y., Yuhashi, H., Koguchi, T.: Regulating ruminative web browsing based on the counterbalance modeling approach. Front. Artif. Intell. (2022). https://doi.org/10.3389/frai.2022.741610

  9. Ohno, T.: One-point calibration gaze tracking method. In: Proceedings of the 2006 Symposium on Eye Tracking Research and Applications, pp. 34–34 (2006)

    Google Scholar 

  10. Panova, T., Lleras, A.: Avoidance or boredom: negative mental health outcomes associated with use of information and communication technologies depend on users’ motivations. Comput. Hum. Behav. 58, 249–258 (2016)

    Article  Google Scholar 

  11. Picard, R.W.: Affective computing: challenges. Int. J. Hum.-Comput. Stud. 59(1–2), 55–64 (2003)

    Article  Google Scholar 

  12. Valstar, M.: Automatic behaviour understanding in medicine. In: Proceedings of the 2014 Workshop on Roadmapping the Future of Multimodal Interaction Research including Business Opportunities and Challenges, pp. 57–60 (2014)

    Google Scholar 

  13. Van Vugt, M.K., Taatgen, N.A., Sackur, J., Bastian, M., Borst, J., Mehlhorn, K.: Modeling mind-wandering: a tool to better understand distraction. In: Proceedings of the 13th International Conference on Cognitive Modeling, pp. 252–257. University of Groningen Groningen, Netherlands (2015)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Shizuoka University, 3-5-1 Johoku, Naka-ku, Hamamatsu, Japan

    Giri Basanta Raj, Junya Morita & Thanakit Pitakchokchai

Authors
  1. Giri Basanta Raj
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  2. Junya Morita
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  3. Thanakit Pitakchokchai
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Corresponding author

Correspondence to Junya Morita .

Editor information

Editors and Affiliations

  1. Graduate School of System Design, Tokyo Metropolitan University, Hino, Tokyo, Japan

    Yasufumi Takama

  2. Graduate School of Economics, Osaka University, Toyonaka, Osaka, Japan

    Naohiro Matsumura

  3. Faculty of Business and Commerce, Kansai University, Osaka, Japan

    Katsutoshi Yada

  4. Faculty of Informatics, Kansai University, Takatsuki, Osaka, Japan

    Mitsunori Matsushita

  5. Department of Applied Computer Science, Tokyo Polytechnic University, Atsugi, Kanagawa, Japan

    Daisuke Katagami

  6. Division of Behavioral Science, Chiba University, Chiba, Japan

    Akinori Abe

  7. Department of Intelligence Science and Technology, Kyoto University, Kyoto, Japan

    Hisashi Kashima

  8. Institute of Industrial Science, The University of Tokyo, Meguro-ku, Tokyo, Japan

    Toshihiro Hiraoka

  9. Department of Computer Science and Engineering, Nagoya Institute of Technology, Nagoya, Japan

    Takahiro Uchiya

  10. Graduate School of Information Science and Technology Sapporo Hokkaido Japan, Hokkaido University, Sapporo, Hokkaido, Japan

    Rafal Rzepka

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Raj, G.B., Morita, J., Pitakchokchai, T. (2022). Gaze Analysis on the Effect of Intervention on Ruminative Web Browsing. In: Takama, Y., et al. Advances in Artificial Intelligence. JSAI 2021. Advances in Intelligent Systems and Computing, vol 1423. Springer, Cham. https://doi.org/10.1007/978-3-030-96451-1_11

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