Sentiment Information

Sentiment information extraction and analysis focuses on identifying and interpreting emotional expressions within text and other modalities, aiming to understand the underlying sentiment and its nuances. Current research emphasizes fine-grained sentiment analysis, including aspect-based sentiment analysis and implicit sentiment detection, often employing large language models (LLMs) and generative models with techniques like instruction tuning and retrieval-based example ranking to improve accuracy and efficiency. These advancements have significant implications for various fields, including market research, financial forecasting, and the development of more equitable and unbiased natural language processing systems.