Scopus Indexed Publications

Paper Details


Title
Analyzing the Impact of Facebook Addiction on Academic Performance Using Machine Learning Techniques

Author
Md Ezaz Ahmed, Hemayet Hossain Tuhin, Md Abdul Kayum, Md. Firoz Hasan, Md. Jhirul Islam,

Email

Abstract

Social networking sites are becoming an essential part of modern society and have an enormous impact on user's daily life and their academic success. Facebook continues to be the most widely used of these systems, especially among students. A total of 2,222 Bangladeshi Facebook users completed the Google Forms survey which analyzed Facebook addiction effects on academic work and learning. The data was analyzed using a machine learning-based technique, testing different models. Gradient Boosting Classifier achieved 94.5% as its best prediction outcome. These results indicate a robust connection between Facebook usage and the possibility of addiction, indicating that higher usage significantly increases the chance of adopting addictive behaviors. Also indicate how Facebook addiction affects academic concentration and performance, highlighting the importance of social media management techniques that encourage enhanced academic achievement. 


Keywords

Journal or Conference Name
2025 IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking, QPAIN 2025

Publication Year
2025

Indexing
scopus