Digital Well-Being Analytics: Social Media, AI, and Mental Health

Abstract

The quick evolution of social media and digital ecosystems based on artificial intelligence (AI) altered the trend in human interaction, communication, and self-expression dramatically. With the introduction of these technologies providing the new opportunities of flexibility in connection and customization of the user, the issue of their impact on mental health and general digital well-being has grown in concern. The authors examine the intricate relationship between the activities of the social media use along with the artificial intelligence-based algorithms and the mental health outcomes according to the digital well-being analytics in this study. The paper will explain these algorithms content curation, engagement optimization algorithm, and data-based personalization and their involvement in the psychological states of anxiety, depression, self-esteem, and social comparison through mixed methods study, a mixture of quantitative behavioral analytics and the qualitative analysis of user perception. The paper will also evaluate the possibility of applying AI as a causative element of digital stress and a prevention and treatment instrument through sentiment-based information, danger prediction algorithms and tailored suggestions of well-being.The findings will endeavor to provide a universal model of AI twofold role in setting digital mental health outcomes. The research can be utilized in the development of ethical AI-driven models of well-being, policy-level reformulations, and principles of platform design that can help make the Internet a healthier place. Lastly, this paper shows that there is need of responsible technological innovation which will balance the metrics of engagement as well as take into account the psychological sustainability in the digital age.