Leveraging Sentiment Analysis and Emotion Detection for Mental Health Insights

This paper aims to establish a comprehensive analysis of mental health patient reviews using various NLP models, to derive insights and propose improvements that will lead to the enhancement of various mental health facilities. These NLP techniques were further used to categorize key themes such as doctor behaviour, communication and cost. A thorough correlation analysis was also conducted, understanding the relationship between various themes and how their frequency affects the overall patient satisfaction. The findings indicate that attentive listening, respectful staff behavior, and affordable services are critical to improving patient satisfaction. While speaking of mental health is still a taboo in various places, it is important to understand the frequency of the rising mental health related cases such as depression, anxiety, stress and social stigma associated with it. It is indeed much more important to provide better resources and lend understanding hand to the unaddressed mental health problems that are prevalent in various countries and places.