Prediction of Smart Phone Addiction among Students Using Gradient Boosting Algorithm

Kondanna Kanamaneni, P. Vasundhara, B. Sruthi, M. Subahan, K. Santosh Kumar

2025

Abstract

The increasing prevalence of electronic gadgets in daily life has brought significant changes to the lifestyle and habits of students. While these gadgets offer undeniable benefits for education, communication, and entertainment, they also pose risks of addiction, negatively impacting student’s academic performance, mental health, and social interactions. This project aims to utilize machine learning algorithms to predict the levels of Smart phone addiction among individuals. Smart Phone addiction is a growing concern in modern society, with adverse effects on mental health and productivity. This project focuses on using various predictive models to classify the addiction level into categories such as low, moderate, and high. This model uses Multiple Machine learning algorithms, including Gradient Boosting Algorithm, Random Forest Algorithm are employed to train models on the dataset. The proposed System used to analyze diverse factors such as screen time, sleep patterns, and academic performance. These algorithms enable accurate predictions and personalized recommendations, fostering proactive interventions. The performance of these models is evaluating using key metrics such as accuracy, precision, recall, and F-score. The results are visualized through confusion matrices and classification reports.

Paper Citation

in Harvard Style

Kanamaneni K., Vasundhara P., Sruthi B., Subahan M. and Kumar K. (2025). Prediction of Smart Phone Addiction among Students Using Gradient Boosting Algorithm. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 78-86. DOI: 10.5220/0013892100004919

in Bibtex Style

@conference{icrdicct`2525,
author={Kondanna Kanamaneni and P. Vasundhara and B. Sruthi and M. Subahan and K. Kumar},
title={Prediction of Smart Phone Addiction among Students Using Gradient Boosting Algorithm},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={78-86},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013892100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Prediction of Smart Phone Addiction among Students Using Gradient Boosting Algorithm
SN - 978-989-758-777-1
AU - Kanamaneni K.
AU - Vasundhara P.
AU - Sruthi B.
AU - Subahan M.
AU - Kumar K.
PY - 2025
SP - 78
EP - 86
DO - 10.5220/0013892100004919
PB - SciTePress