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Stock Market Sentiment Classification from FinTech News

Sentiment classification is an instrument used for predicting stock price movement. This paper presents a comparison of sentiment classification performance using machine learning techniques consisting of the Naïve Bayes classifier and support vector machine (SVM) to provide a positive, neutral, or negative sentiment in Thai FinTech news and opinions on the tweet corpus. Accordingly, machine learning algorithms are employed to analyze how tweets correlate with stock market price behavior. Finally, the actual and prediction errors are examined by evaluating classifier performance. The results show that the Support Vector Machine has a better performance than the Naïve Bayes classifier.