It learns word representations and sentiment classification at the same time. Traditionally, word representations are learned by looking at surrounding words.

It learns word representations and sentiment classification at the same time. Traditionally, word representations are learned by looking at surrounding words. So "good" and "bad" will have similar word representations. By training on sentiment, similar sentiment words should be clustered together.