NLP and Sentiment analysis are increasingly used in different fields. Although these methods still take time to mature, they are the trend of unstructured data analysis. They are worthy of our research. Furthermore, today data science plays an essential role in the stock trading industry. Studying data processing, data analysis, and machine learning algorithms will help us understand how data science impacts the financial industry. Therefore, I conduct this case study project regarding stock sentiment analysis. This project has two parts: The first part uses the NLP technique to perform sentiment analysis on authoritative financial reports published by public companies. The analysis focuses on studying how the market’s sentiment towards the company changes over time. The second part is to use deep learning algorithms to predict the sentiment of investment social media posts. This project aims to help better investors make investment decisions by predicting and analyzing stock market sentiment. The data used in the project is from companies’10-k financial statements and the investment social media Stocktwits.