Stocksight uses Elasticsearch to store and index Twitter feeds and news headlines, then applies Python NLP libraries including NLTK, TextBlob, and VADER to perform sentiment analysis on the text. The system correlates emotional signals from social media and news sources with stock price movements to generate predictions. It integrates with the Twitter streaming API via tweepy for real-time data ingestion and Kibana for visualization.