Sentiment Analysis

Sentiment analysis is a task in the field of natural language processing aimed at classifying the emotional tone of given texts, typically categorizing them as positive, negative, or neutral. This task can be achieved through machine learning, dictionary-based methods, and hybrid approaches. In recent years, deep learning technologies such as RoBERTa and T5 have been widely used to train high-performance sentiment classifiers, with evaluation metrics including F1 score, recall, and precision. Sentiment analysis is not only used for social media monitoring but also widely applied in areas like product review analysis and market trend prediction, demonstrating significant application value.