This document summarizes a research paper that aims to perform sentiment analysis on posts and comments on online social networks like Twitter. The proposed system seeks to identify the sentiment behind content posted to determine if users exhibit signs of depression. It will analyze text for positive emotions like happy and negative emotions like sad using machine learning techniques. The results will then classify the degree of negative sentiment and potential depression displayed by the user. The system architecture involves collecting social media data, filtering out noise, comparing text to stored emotional words, and generating a result that calculates sentiment scores and ranks emotions displayed in the content.