Дослідження методів аналізу емоційного забарвлення текстів

Abstract

This work is devoted to the study of methods for determining the emotional coloring of texts. Traditional approaches, such as dictionary-based and rule-based methods, as well as modern machine learning techniques, including neural networks and transformer models were analyzed. Special attention is given to the challenges of sentiment analysis, such as sarcasm, irony, and contextual word meanings. The study highlights the advantages and limitations of different approaches and emphasizes the need for optimizing transformer models for resource-limited environments.