Factors on Students Social Media Addiction and its Outcomes Based on Multiple Linear Regression Model

Abstract

Social media becomes increasingly important for students for entertainment, learning and social activities. However, more students are diagnosed as addicted to social media, influencing their daily life. Hence, this paper analyzes a cross-national data set of students from high school or university. By applying multiple linear regression model, this study explored the relationship between eleven different factors and students’ addiction level, trying to find out what were the major causes of students’ social media addiction (SMA) and whether it would have detrimental effects on students’ daily life, including academic performance and mental health. To ensure the accuracy of data analysis, collinearity diagnosis is applied. In conclusion, Age, Academic Level and Average Daily Use Hours are the major causes of SMA. Students with a younger age or lower educational level have a higher risk of addicted to social media. Longer usage hours or higher frequency also alleviates the tendency. SMA would detrimentally affect students’ sleep quality and academic performance, and it also leads to mental illness. However, there was no evident proof that gender or relationship status is related with addiction.