SentiMetry: A Development of Emotional Wellness Web Application Using AI-Driven Sentiment Analysis

In a time when mental health issues are becoming more widespread, creative solutions combining psychology and technology are crucial. This study presents SentiMetry, an online application for emotional well-being that combines sophisticated AI-driven sentiment analysis with conventional journaling. SentiMetry, which has its roots in Sustainable Development Goal 3, seeks to improve mental health by offering users tailored support and insights according to their emotional states. SentiMetry employs machine learning models like EmoRoBERTa, Logistic Regression, and a Bidirectional LSTM-Based RNN Model to detect users' emotions precisely and provide customized feedback that promotes resilience and self-awareness. Users may travel their emotional landscapes in a supportive atmosphere thanks to the application's intuitive design and sympathetic answers. SentiMetry has the potential to be a valuable tool for emotional well-being and self-awareness, as evidenced by user testing findings, where users found the app to be impactful and recommended it to others. SentiMetry makes a significant contribution to mental health, even if it has drawbacks, including privacy issues and a reliance on technology. SentiMetry is a promising first step toward using technology to promote sustainable development objectives and mental health.