Emotional Analysis on Social Media Platform

In this paper, we also do a affect and emotion analysis A highly sophisticated Natural Language Processing (NLP) based Analytics System (NLP and machine learning) to analyse how people feel about it Twitter, same for other social media campaigns on environmental problems of prejudices like Reddit, YouTube (2014-2023 data). The The sentiment classification is using the Support Vector Machine (SVM) Classification with 72 % precision, sentiments positive, negative or neutral as well extract emotions for fear, trust and anticipation. Results in the analysis of negative emotions as reported public concern over ecologi degradation of natural settings, with the time trends reaching peaks in key natural events or policy changes Occurring We had a system upscalings over baselines as VADER, for laters the problem is still that it does not understand sarcasm nor the context. Next im enhancement later can be using transformer-based models with BERT for enhanced contextual understanding and enhancing emotional categories (for interpretation) in addition, useful inputs for interventions set-up by stakeholders to produce relevant awareness : ) for a fair world.