Project write-up for a tool to classify tweet sentiment (positive, negative, neutral) to surface public-opinion trends.
Status: Write-up only — the implementation notebook/scripts are being migrated into this repository. Treat this as a project summary rather than a finished codebase.
Approach: Clean and tokenize tweet text, extract features, and classify sentiment using a trained model, then aggregate results to surface trends across a set of tweets.
Tools: NLTK, spaCy, TextBlob, Scikit-learn, TensorFlow, Tweepy.
Author: Rishabh Singh