#GAMEADDICTED: A Machine Learning Framework for Digital Game Addiction Detection and Early Intervention

#GAMEADDICTED: A Machine Learning Framework for Digital Game Addiction Detection and Early Intervention

This study addresses the growing concern of digital game addiction (DGA) by developing an information system for detection and early intervention, to predict an individual’s propensity toward DGA. The study employed machine learning models to process unstructured data collected from onlin...

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Bibliographic Details
Main Authors: Esra Kahya Ozyirmidokuz, Bekir Asim Celik, Eduard Alexandru Stoica
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Digital game addiction
data analytics
early diagnosis
machine learning
text classification
natural language processing
Online Access:https://ieeexplore.ieee.org/document/11075684/
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https://ieeexplore.ieee.org/document/11075684/

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