Sentiment analysis is a computational field and methodological approach within natural language processing (NLP) focused on systematically identifying, extracting, and quantifying subjective information from textual data. It investigates opinions, emotions, sentiments, and attitudes expressed towards entities, topics, or events, typically categorizing them by polarity (positive, negative, neutral) and intensity using automated techniques. This process is significant for understanding public opinion, market trends, and facilitating data-driven insights across various domains.