Емоціональна оцінка новин для прогнозування курсу біткоїну

Abstract

This article showcases the use of news sentiment analysis to predict Bitcoin prices. It offers a comprehensive analysis at the intersection of finance and machine learning. The research includes data collection and pre-processing, sentiment analysis, feature development, and model training The article highlights the effectiveness of improved efficiency in identifying complex relationships in cryptocurrency markets. Tuning and estimating hyperparameters further improves the accuracy of the model. Although market volatility presents challenges, the results emphasize the importance of forecasting for investors and cryptocurrency researchers.