스마트폰 과의존 판별을 위한 기계 학습 기법의 응용

• 영문명: Application of Machine Learning Techniques for Problematic Smartphone Use
• 발행기관: 강원대학교 경영경제연구소
• 저자명: 김우성 한준희
• 간행물 정보: 『아태비즈니스연구』제13권 제3호, 293~309쪽, 전체 17쪽
• 주제분류: 인문학 > 문학
• 파일형태: PDF
• 발행일자: 2022.09.30

영문 초록

Purpose - The purpose of this study is to explore the possibility of predicting the degree of smartphone overdependence based on mobile phone usage patterns. Design/methodology/approach - In this study, a survey conducted by Korea Internet and Security Agency(KISA) called “problematic smartphone use survey” was analyzed. The survey consists of 180 questions, and data were collected from 29,712 participants. Based on the data on the smartphone usage pattern obtained through the questionnaire, the smartphone addiction level was predicted using machine learning techniques. k-NN, gradient boosting, XGBoost, CatBoost, AdaBoost and random forest algorithms were employed. Findings - First, while various factors together influence the smartphone overdependence level, the results show that all machine learning techniques perform well to predict the smartphone overdependence level. Especially, we focus on the features which can be obtained from the smartphone log data (without psychological factors). It means that our results can be a basis for diagnostic programs to detect problematic smartphone use. Second, the results show that information on users’ age, marriage and smartphone usage patterns can be used as predictors to determine whether users are addicted to smartphones. Other demographic characteristics such as sex or region did not appear to significantly affect smartphone overdependence levels. Research implications or Originality - While there are some studies that predict smartphone overdependence level using machine learning techniques, but the studies only present algorithm performance based on survey data. In this study, based on the information gain measure, questions that have more influence on the smartphone overdependence level are presented, and the performance of algorithms according to the questions is compared. Through the results of this study, it is shown that smartphone overdependence level can be predicted with less information if questions about smartphone use are given appropriately.

목차

Ⅰ. 서론

Ⅱ. 문헌 조사

Ⅲ. 데이터 및 연구방법론

Ⅳ. 분석 결과

Ⅴ. 결론

References

키워드

Smartphone Overdependence Problematic smartphone use Machine learning Predictor.