Classify documents (e.g., reviews) based on the overall sentiments expressed by opinion holders (authors),
Positive, negative, and (possibly) neutral
Since in our model an object O itself is also a feature, then sentiment classification essentially determines the opinion expressed on O in each document (e.g., review).
Similar but different from topic-based text classification.
In topic-based text classification, topic words are important.
In sentiment classification, sentiment words are more important, e.g., great, excellent, horrible, bad, worst, etc.