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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).

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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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