Exploratory data analysis and machine learning-based assessment of social media addiction and its impact on academic performance and mental health among students.

This study investigates social media addiction among students. It includes definitions, ways to measure it, how common it is, and its effects on mental health and academic performance. A focused review of literature from 2018 to 2025 gathers systematic reviews, meta-analyses, psychometric studies, and research that connects problematic social media use to issues like mental health problems, sleep disruptions, and academic results. The article also provides a method for analyzing student-level social media addiction data. It discusses common findings in datasets and offers recommendations for educators and policymakers based on evidence. Using data from 705 participants across 110 countries, this study combines a thorough literature review, dataset-driven exploratory data analysis (EDA), and correlational modeling. The results show strong connections between social media addiction, academic success, sleep, and mental health. The EDA reveals gender differences in usage, regional differences in platform preferences, and clear links between addiction and poorer sleep quality and mental health. These findings align with global research and suggest the potential value of targeted digital well-being interventions among students.