Stock Sentiment Analysis Project: Comparing Rule-Based Models and Machine Learning Methods in Financial Text Mining Applications

Introduction / Main Floor: Stock Sentiment Analysis Project: Comparing Rule-Based Models and Machine Learning Methods in Financial Text Mining Applications

In-depth analysis of a sentiment analysis project based on 4838 financial news headlines, exploring the performance differences and applicable scenarios between rule-based methods like VADER and TextBlob and TF-IDF machine learning classifiers in financial sentiment prediction.