This research paper explores the potential of ChatGPT in predicting stock market trends through Twitter sentiment analysis. The study investigates whether ChatGPT's advanced language understanding capabilities can effectively analyze social media sentiment to forecast stock movements, specifically focusing on Microsoft and Google as case studies. By classifying tweets into positive, negative, or neutral sentiment categories and correlating these with subsequent stock performance, the research demonstrates ChatGPT's ability to extract meaningful financial signals from unstructured social media data.

The methodology involves using ChatGPT to perform sentiment analysis on Twitter data, followed by statistical correlation analysis with stock price movements. The findings reveal a positive relationship between ChatGPT's sentiment evaluations and next-day stock performance for both companies, suggesting that AI-driven sentiment analysis can provide valuable predictive insights. This research contributes to the growing body of literature on AI applications in finance, highlighting ChatGPT's adaptability beyond conversational tasks and underscoring the increasing importance of artificial intelligence in enhancing financial market forecasting capabilities.