Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.

Journal: Frontiers in public health
PMID: 38827621

Abstract

BACKGROUND: By using algorithms and Machine Learning - ML techniques, the aim of this research was to determine the impact of the following factors on the development of Problematic Internet Use (PIU): sociodemographic factors, the intensity of using the Internet, different contents accessed on the Internet by adolescents, adolescents' online activities, life habits and different affective temperament types.

Authors

  • Jelena Jović
    Department of Preventive Medicine, Faculty of Medicine, University of Pristina in Kosovska Mitrovica, Kosovska Mitrovica, Serbia.
  • Aleksandar Ćorac
    Department of Preventive Medicine, Faculty of Medicine, University of Pristina in Kosovska Mitrovica, Kosovska Mitrovica, Serbia.
  • Aleksandar Stanimirović
    Computer Science, Faculty of Electronic Engineering, University of Niš, Niš, Serbia.
  • Mina Nikolić
    Computer Science, Faculty of Electronic Engineering, University of Niš, Niš, Serbia.
  • Marko Stojanović
    Department of Epidemiology, Faculty of Medicine, University of Niš, Niš, Serbia.
  • Zoran Bukumirić
    Institute of Medical Statistics and Informatics, Faculty of Medicine, University of Belgrade, Belgrade, Serbia.
  • Dragana Ignjatović Ristić
    Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia.

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