IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i12p6458-d575056.html
   My bibliography  Save this article

Prediction of Problematic Smartphone Use: A Machine Learning Approach

Author

Listed:
  • Juyeong Lee

    (Department of Industrial Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea)

  • Woosung Kim

    (College of Business Administration, Konkuk University, Seoul 05029, Korea)

Abstract

While smartphone addiction is becoming a recent concern with the exponential increase in the number of smartphone users, it is difficult to predict problematic smartphone users based on the usage characteristics of individual smartphone users. This study aimed to explore the possibility of predicting smartphone addiction level with mobile phone log data. By Korea Internet and Security Agency (KISA), 29,712 respondents completed the Smartphone Addiction Scale developed in 2017. Integrating basic personal characteristics and smartphone usage information, the data were analyzed using machine learning techniques (decision tree, random forest, and Xgboost) in addition to hypothesis tests. In total, 27 variables were employed to predict smartphone addiction and the accuracy rate was the highest for the random forest (82.59%) model and the lowest for the decision tree model (74.56%). The results showed that users’ general information, such as age group, job classification, and sex did not contribute much to predicting their smartphone addiction level. The study can provide directions for future work on the detection of smartphone addiction with log-data, which suggests that more detailed smartphone’s log-data will enable more accurate results.

Suggested Citation

  • Juyeong Lee & Woosung Kim, 2021. "Prediction of Problematic Smartphone Use: A Machine Learning Approach," IJERPH, MDPI, vol. 18(12), pages 1-13, June.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6458-:d:575056
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/12/6458/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/12/6458/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Sheila Yu & Steve Sussman, 2020. "Does Smartphone Addiction Fall on a Continuum of Addictive Behaviors?," IJERPH, MDPI, vol. 17(2), pages 1-21, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mei-Feng Huang & Yu-Ping Chang & Wei-Hsin Lu & Cheng-Fang Yen, 2022. "Problematic Smartphone Use and Its Associations with Sexual Minority Stressors, Gender Nonconformity, and Mental Health Problems among Young Adult Lesbian, Gay, and Bisexual Individuals in Taiwan," IJERPH, MDPI, vol. 19(9), pages 1-12, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Siti Rubiaehtul Hassim & Wan Nor Arifin & Yee Cheng Kueh & Nor Azwany Yaacob, 2020. "Confirmatory Factor Analysis of the Malay Version of the Smartphone Addiction Scale among Medical Students in Malaysia," IJERPH, MDPI, vol. 17(11), pages 1-10, May.
    2. Daria J. Kuss & Lydia Harkin & Eiman Kanjo & Joel Billieux, 2018. "Problematic Smartphone Use: Investigating Contemporary Experiences Using a Convergent Design," IJERPH, MDPI, vol. 15(1), pages 1-16, January.
    3. Melina A. Throuvala & Mark D. Griffiths & Mike Rennoldson & Daria J. Kuss, 2019. "A ‘Control Model’ of Social Media Engagement in Adolescence: A Grounded Theory Analysis," IJERPH, MDPI, vol. 16(23), pages 1-18, November.
    4. 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.
    5. Majid Altuwairiqi & Nan Jiang & Raian Ali, 2019. "Problematic Attachment to Social Media: Five Behavioural Archetypes," IJERPH, MDPI, vol. 16(12), pages 1-36, June.
    6. Marta Tremolada & Lucio Silingardi & Livia Taverna, 2022. "Social Networking in Adolescents: Time, Type and Motives of Using, Social Desirability, and Communication Choices," IJERPH, MDPI, vol. 19(4), pages 1-15, February.
    7. Alexis M. McCarroll & Bree E. Holtz & Dar Meshi, 2021. "Searching for Social Media Addiction: A Content Analysis of Top Websites Found through Online Search Engines," IJERPH, MDPI, vol. 18(19), pages 1-15, September.
    8. Taesoo Cho & Taeyoung Cho & Hyunjun Choi & Sungchul Yang & Hao Zhang, 2023. "User Satisfaction Study for Sustainability of YouTube Content Quality: Focusing on Ski Technology," Businesses, MDPI, vol. 3(1), pages 1-15, January.
    9. Kai W. Müller & Jennifer Werthmann & Manfred E. Beutel & Klaus Wölfling & Boris Egloff, 2021. "Maladaptive Personality Traits and Their Interaction with Outcome Expectancies in Gaming Disorder and Internet-Related Disorders," IJERPH, MDPI, vol. 18(8), pages 1-11, April.
    10. Kane J. Smith & Gurpreet Dhillon & Brigid A. Otoo, 2022. "iGen User (over) Attachment to Social Media: Reframing the Policy Intervention Conversation," Information Systems Frontiers, Springer, vol. 24(6), pages 1989-2006, December.
    11. Yun-Hsuan Chang & Yun-Ting Lee & Shulan Hsieh, 2019. "Internet Interpersonal Connection Mediates the Association between Personality and Internet Addiction," IJERPH, MDPI, vol. 16(19), pages 1-11, September.
    12. Élodie Verseillié & Stéphanie Laconi & Henri Chabrol, 2020. "Pathological Traits Associated to Facebook and Twitter among French Users," IJERPH, MDPI, vol. 17(7), pages 1-9, March.
    13. Dong-Hyun Choi & Young-Su Jung, 2022. "Temperament, Character and Cognitive Emotional Regulation in the Latent Profile Classification of Smartphone Addiction in University Students," Sustainability, MDPI, vol. 14(18), pages 1-16, September.
    14. Shuo Zhang & Tat Y. Chan & Xueming Luo & Xiaoyi Wang, 2022. "Time-Inconsistent Preferences and Strategic Self-Control in Digital Content Consumption," Marketing Science, INFORMS, vol. 41(3), pages 616-636, May.
    15. Olatz Lopez-Fernandez, 2021. "Emerging Health and Education Issues Related to Internet Technologies and Addictive Problems," IJERPH, MDPI, vol. 18(1), pages 1-19, January.
    16. Xavier Carbonell & Andrés Chamarro & Ursula Oberst & Beatriz Rodrigo & Mariona Prades, 2018. "Problematic Use of the Internet and Smartphones in University Students: 2006–2017," IJERPH, MDPI, vol. 15(3), pages 1-13, March.
    17. Antonio-José Moreno-Guerrero & Inmaculada Aznar-Díaz & Pilar Cáceres-Reche & Antonio-Manuel Rodríguez-García, 2020. "Do Age, Gender and Poor Diet Influence the Higher Prevalence of Nomophobia among Young People?," IJERPH, MDPI, vol. 17(10), pages 1-13, May.
    18. da Silva, Filipa Pires & Jerónimo, Helena Mateus & Henriques, Paulo Lopes & Ribeiro, Joana, 2024. "Impact of digital burnout on the use of digital consumer platforms," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    19. Kuan-Ying Hsieh & Ray C. Hsiao & Yi-Hsin Yang & Kun-Hua Lee & Cheng-Fang Yen, 2019. "Relationship between Self-Identity Confusion and Internet Addiction among College Students: The Mediating Effects of Psychological Inflexibility and Experiential Avoidance," IJERPH, MDPI, vol. 16(17), pages 1-11, September.
    20. Hiu Yan Wong & Hoi Yi Mo & Marc N. Potenza & Mung Ni Monica Chan & Wai Man Lau & Tsz Kwan Chui & Amir H. Pakpour & Chung-Ying Lin, 2020. "Relationships between Severity of Internet Gaming Disorder, Severity of Problematic Social Media Use, Sleep Quality and Psychological Distress," IJERPH, MDPI, vol. 17(6), pages 1-13, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:12:p:6458-:d:575056. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.