StockFusion: AI-Powered Stock Market Prediction using LSTM and Sentiment Analysis

Abstract

Stock market prediction remains one of the most challenging problems due to market volatility, external socio-economic factors, and investor sentiment. Traditional statistical models often fail to capture complex nonlinear patterns, making deep learning-based approaches more effective. StockFusion is an AI-driven system that integrates Long Short-Term Memory (LSTM) networks for time-series stock price forecasting and Natural Language Processing (NLP)-based sentiment analysis for real-time market insights. By combining these techniques, the system provides enhanced accuracy in stock prediction. This paper discusses the architecture, implementation, and experimental evaluation of StockFusion, demonstrating that the hybrid approach of price prediction and sentiment analysis improves decision-making for investors and traders.