The three main sentiment analysis methods are rule-based analysis, machine learning-based analysis, and lexicon-based analysis. Rule-based analysis relies on predefined rules and patterns to determine sentiment, while machine learning-based analysis involves training models on labeled data to predict sentiment labels. Lexicon-based analysis utilizes sentiment lexicons or dictionaries to assign sentiment scores to words or phrases based on their semantic meanings and associations. Each method has its strengths and limitations, and the choice depends on the specific requirements of the sentiment analysis task.