This project provides a FastAPI-based web service for Twitter sentiment analysis using three different models:

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NLP, Text Mining on Social Media Data Facebook Graph API Noise removal, Lexicon Normalization(Stemming) Tokenization: Convert text into tokens. Unigram, bi-gram, Tri-grams Feature Engineering(Text to Features):Syntactical, Entity, Statistical Syntactical Parsing: Part of Speech Tagging Statistical Parsing: Document Matrix Entity Parsing :Topic Modelling Other Statistics:Frequency counts Sentiment Analysis:Positive/Negative Language Detection:Detect/Translate Network Analysis and Recommendation:Targeted Ads to Friends