Sentiment analysis is a branch of Natural Language Processing (NLP) that focuses on analyzing and understanding people's opinions, feelings, and attitudes towards a particular subject or topic. It involves extracting and examining subjective information from text data, such as reviews, social media posts, and customer feedback, to determine whether the sentiment expressed is positive, negative, or neutral. Sentiment analysis uses various techniques, such as machine learning algorithms, keyword analysis, and deep learning models, to classify and quantify sentiments and emotions in text data. This research area is widely used in marketing, customer service, and social media monitoring to gain insights into how people perceive and react to different products, services, or events.