A New Method for Sentiment Classification in Text Retrieval

Traditional text categorization is usually a topic-based task, but a subtle demand on information retrieval is to distinguish between positive and negative view on text topic. In this paper, a new method is explored to solve this problem. Firstly, a batch of Concerned Concepts in the researched domain is predefined. Secondly, the special knowledge representing the positive or negative context of these concepts within sentences is built up. At last, an evaluating function based on the knowledge is defined for sentiment classification of free text. We introduce some linguistic knowledge in these procedures to make our method effective. As a result, the new method proves better compared with SVM when experimenting on Chinese texts about a certain topic.