Predictive Modelling of Human Emotions in Social Media from Sentiment Analysis

More than 4.8 billion people use social media worldwide and revolutionise the notion of digital communication with huge amounts of textual data production. Sentiment analysis is an offspring of NLP, which gathers emotions from this data, making it a golden mine of knowledge about what's going on in people's heads. This article explores how to predict human minds' emotions with social media messages. Techniques involved here include data preprocessing, text cleaning, and visualization. The research attempt will be to classify emotions with high accuracy using deep learning and machine learning models. This is why sentiment analysis has become important in other fields, for example, in marketing, the assessment of mental health, and the tracking of public opinion. Since correctness is now better than 85% with the advancements made in deep learning [2], data-driven decisions and behavioural prediction can be based on sentiment analysis. This study points out that understanding human emotion through sentiment analysis can be quite valuable for a business, a researcher, and even a policymaker.