Sentiment analysis uses natural language processing (NLP) and machine learning algorithms to analyze text. The process involves several steps: 1. Data Collection: Gathering text data from various sources. 2. Preprocessing: Cleaning the data to remove noise and irrelevant information. 3. Sentiment Detection: Classifying text as positive, negative, or neutral. 4. Scoring: Assigning a sentiment score to quantify the emotional tone.