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Smartphone dependence classification using tensor factorization

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  • Jingyun Choi
  • Mi Jung Rho
  • Yejin Kim
  • In Hye Yook
  • Hwanjo Yu
  • Dai-Jin Kim
  • In Young Choi

Abstract

Excessive smartphone use causes personal and social problems. To address this issue, we sought to derive usage patterns that were directly correlated with smartphone dependence based on usage data. This study attempted to classify smartphone dependence using a data-driven prediction algorithm. We developed a mobile application to collect smartphone usage data. A total of 41,683 logs of 48 smartphone users were collected from March 8, 2015, to January 8, 2016. The participants were classified into the control group (SUC) or the addiction group (SUD) using the Korean Smartphone Addiction Proneness Scale for Adults (S-Scale) and a face-to-face offline interview by a psychiatrist and a clinical psychologist (SUC = 23 and SUD = 25). We derived usage patterns using tensor factorization and found the following six optimal usage patterns: 1) social networking services (SNS) during daytime, 2) web surfing, 3) SNS at night, 4) mobile shopping, 5) entertainment, and 6) gaming at night. The membership vectors of the six patterns obtained a significantly better prediction performance than the raw data. For all patterns, the usage times of the SUD were much longer than those of the SUC. From our findings, we concluded that usage patterns and membership vectors were effective tools to assess and predict smartphone dependence and could provide an intervention guideline to predict and treat smartphone dependence based on usage data.

Suggested Citation

  • Jingyun Choi & Mi Jung Rho & Yejin Kim & In Hye Yook & Hwanjo Yu & Dai-Jin Kim & In Young Choi, 2017. "Smartphone dependence classification using tensor factorization," PLOS ONE, Public Library of Science, vol. 12(6), pages 1-12, June.
    • Handle: RePEc:plo:pone00:0177629
    DOI: 10.1371/journal.pone.0177629
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    Cited by:

    1. Jeong Hye Park & Minjung Park, 2021. "Smartphone use patterns and problematic smartphone use among preschool children," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-12, March.
    2. Sara Thomée, 2018. "Mobile Phone Use and Mental Health. A Review of the Research That Takes a Psychological Perspective on Exposure," IJERPH, MDPI, vol. 15(12), pages 1-25, November.
    3. Flourensia Sapty Rahayu & Lukito Edi Nugroho & Ridi Ferdiana & Djoko Budiyanto Setyohadi, 2020. "Research Trend on the Use of IT in Digital Addiction: An Investigation Using a Systematic Literature Review," Future Internet, MDPI, vol. 12(10), pages 1-23, October.

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