Abstract:

This research delves into the merging realms of mental health and technology, specifically targeting the identification of personality disorders through the analysis of social media data and advanced deep learning methodologies. By synthesizing insights from key studies, we utilize a comprehensive dataset comprising 1260 individuals to harness the combined power of conventional techniques such as sentiment analysis and state-of-the-art deep learning models, including Decision Trees, Random Forests, and Neural Networks. Our discoveries underscore the efficacy of linguistic patterns and deep learning approaches in identifying markers of personality disorders. This study contributes significantly to the ongoing dialogue surrounding the ethical integration of technology in mental health initiatives, advocating for sustained exploration and development of diagnostic tools and interventions.