SENTIMENTAL ANALYSICS ON SOCIAL MEDIA

This project aims to combat misinformation on social media by developing a system that combines sentimentanalysis, fake news detection, and deep fake recognition. Using VADER lexicon, the sentiment analysis modulewill categorize social media posts into positive, negative, or neutral sentiment. A fake news detection modulewill identify misleading content using advanced techniques, while a deep fake recognition system, powered byPyTorch and LSTM networks, will analyze media for anomalies indicative of synthetic manipulation. Thisintegrated approach seeks to enhance trust and accountability in online information, contributing to a moreinformed and safer digital environment.