Machine Learning Analysis of Social Media’s Impact on Mental Health of Indian Youth

Abstract
This study delves into the complex relationship between various mental health indicators and their influencing factors among Indian youths. It specifically examines how external validation, interactions on social media platforms, and demographic variables such as gender, age, and occupation impact a range of mental health outcomes. These outcomes include experiencing negative thoughts, a disinterest in activities, low self-esteem, the development of eating disorders, disturbances in sleep patterns, symptoms of depression, difficulties in concentration, and feelings of fatigue. Employing the theoretical framework of Social Cognitive Theory, this research utilized an online random sampling method to gather data from a diverse group of 151 Indian youth participants. The findings of this study highlight the significant role that external validation and social media usage play in shaping mental health conditions among the youth. This underscores the critical need for integrating digital literacy components into mental health initiatives, aiming to foster healthier online behaviors and interactions. Furthermore, the study advocates for a holistic approach to mental health care, emphasizing the consideration of the specific needs of various demographic segments. It suggests that future mental health policies and interventions should be culturally sensitive and responsive. The results of this research underscore the pressing necessity for ongoing investigations into these vital dynamics, aiming to better understand and address the mental health challenges faced by Indian youths.
Keywords: Demographics, Machine Learning, Mental Health Outcomes, Indian Youths, Social Media Behaviour.

Author(s): Vengalarao Pachava*, Olusiji Adebola Lasekan, Siva Krishna Golla, Sreeramulu Gosikonda
Volume: 5 Issue: 2 Pages: 623-635
DOI: https://doi.org/10.47857/irjms.2024.v05i02.0592