• Text categorization, in which an entire text is assigned a class from a finite set, includes such tasks as sentiment analysis, spam detection, language identification, and authorship attribution. • Sentiment analysis classifies a text as reflecting the positive or negative orientation (sentiment) that a writer expresses toward some object. • Naive Bayes is a generative model that makes the bag of words assumption (position doesn't matter) and the conditional independence assumption (words are conditionally independent of each other given the class) • Naive Bayes with binarized features seems to work better for many text classification tasks. • Classifiers are evaluated based on precision and recall.