AI-Powered Sentiment Analysis for Real-Time Stock Market Predictions
Abstract
This research explores the integration of AI-powered sentiment analysis with financial data for real-time stock market predictions. A transformer-based model is developed to analyze news articles, social media posts, and market trends. The system achieves a prediction accuracy of 89.7% on historical datasets. The paper highlights the role of sentiment analysis in financial forecasting and its implications for traders and investors.
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