Дослідження методів машинного навчання для визначення тональності текстових даних

Abstract

Machine learning methods for text sentiment detection are studied in this work. Four classification algorithms were implemented and compared: Naive Bayes, Support Vector Machine (SVM), Logistic Regression, and a neural network. The models were trained and tested on a labeled dataset of 1000 text samples. The neural network achieved the highest accuracy of 89.2% and F1-score of 88.9%. The results of this study can be used for automated analysis of customer feedback, social media monitoring, and other applications requiring sentiment detection.