NLP-Based Mental Health Analysis Using WhatsApp Chat

WhatsApp is a popular social media platform which is widely used all over the world to communicate and connect as it allows people to discuss in groups.The discussion logs of WhatsApp can reveal information about user behavior which also tells about the Mental Health of a person.Analysis of the sentiments can help the users in decision making and in the diagnosis the problem of mental health all over the world.This research study is a data analysis initiative designed to uncover patterns in communication, user interactions, and engagement within WhatsApp conversations.By leveraging natural language processing (NLP) and data visualization techniques such as charts, graphs, and word clouds present the data insights in a clear and accessible format.The study aims to evaluate the content, sentiment, and present the data insights in a clear and accessible format.Future sentiment analysis systems aim to detect a wider range of emotions and moods, incorporating contextual understanding and cultural nuances for more nuanced interpretations.These advancements can enhance behavioral analysis, and mental health assessment.In healthcare, sentiment analysis could aid early detection of mental health issues by identifying patterns in expressions and language usage.The analysis of the WhatsApp conversations using NLP and data visualization provides insights into user sentiment, engagement trends, and communication patterns.It supports mental health by identifying early concerns and promoting supportive digital interactions.