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An Ensemble Classifier with Case-Based Reasoning System for Identifying Internet Addiction

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  • Wen-Huai Hsieh

    (Department of Information Management, National Chung Cheng University; Director of Chang-Hua Hospital, Chang-Hua County 51341, Taiwan)

  • Dong-Her Shih

    (Department of Information Management, National Yunlin University of Science & Technology, Douliu 64002, Taiwan)

  • Po-Yuan Shih

    (Department of Finance, National Yunlin University of Science & Technology, Douliu 64002, Taiwan)

  • Shih-Bin Lin

    (Department of Information Management, National Yunlin University of Science & Technology, Douliu 64002, Taiwan)

Abstract

Internet usage has increased dramatically in recent decades. With this growing usage trend, the negative impacts of Internet usage have also increased significantly. One recurring concern involves users with Internet addiction, whose Internet usage has become excessive and disrupted their lives. In order to detect users with Internet addiction and disabuse their inappropriate behavior early, a secure Web service-based EMBAR (ensemble classifier with case-based reasoning) system is proposed in this study. The EMBAR system monitors users in the background and can be used for Internet usage monitoring in the future. Empirical results demonstrate that our proposed ensemble classifier with case-based reasoning (CBR) in the proposed EMBAR system for identifying users with potential Internet addiction offers better performance than other classifiers.

Suggested Citation

  • Wen-Huai Hsieh & Dong-Her Shih & Po-Yuan Shih & Shih-Bin Lin, 2019. "An Ensemble Classifier with Case-Based Reasoning System for Identifying Internet Addiction," IJERPH, MDPI, vol. 16(7), pages 1-17, April.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1233-:d:220546
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    References listed on IDEAS

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    1. Wei-Po Chou & Cheng-Fang Yen & Tai-Ling Liu, 2018. "Predicting Effects of Psychological Inflexibility/Experiential Avoidance and Stress Coping Strategies for Internet Addiction, Significant Depression, and Suicidality in College Students: A Prospective," IJERPH, MDPI, vol. 15(4), pages 1-11, April.
    2. Olatz Lopez-Fernandez, 2018. "Generalised Versus Specific Internet Use-Related Addiction Problems: A Mixed Methods Study on Internet, Gaming, and Social Networking Behaviours," IJERPH, MDPI, vol. 15(12), pages 1-33, December.
    3. Fei Shi, 2015. "Study on a Stratified Sampling Investigation Method for Resident Travel and the Sampling Rate," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-7, March.
    4. Efrim Boritz, J. & No, Won G., 2005. "Security in XML-based financial reporting services on the Internet," Journal of Accounting and Public Policy, Elsevier, vol. 24(1), pages 11-35.
    5. Daria J. Kuss & Mark D. Griffiths, 2011. "Online Social Networking and Addiction—A Review of the Psychological Literature," IJERPH, MDPI, vol. 8(9), pages 1-25, August.
    Full references (including those not matched with items on IDEAS)

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