In traditional text classification tasks, a text T (e.g., document, sentence) are modeled as one bag-of-words and the input vector of the text is constructed from weights of the words (also called terms) 1 ( ,..., ) In this paper, we focus on document-based sentiment classification.
the terms are possibly words, word n-grams, or even phrases extracted from the training data, with N being the number of terms.