Sentiment Analysis (also known as opinion mining) is an NLP technique that determines the emotional tone or attitude expressed in a piece of text​.The goal is to classify text (such as reviews, social media posts, or survey responses) as expressing positive, negative, or neutral sentiment (or sometimes a more fine-grained emotion category). Sentiment analysis uses natural language processing and machine learning to detect subjective information: for example, a model might analyze the words in a product review to conclude whether the reviewer liked the product or not​. Applications of sentiment analysis include brand monitoring (gauging public opinion on social media), customer feedback analysis, and market research, where organizations automatically process large volumes of text to extract insights about attitudes. Modern approaches often use transformer-based language models or specialized lexicons to improve accuracy in detecting sentiment despite nuances like sarcasm or context.