Abstract
This paper presents a new method about Chinese short text sentiment polarity analysis. Introducing a mechanism of biological immunology into the traditional Chinese word sentiment analysis. Artificial immune system is designed to simulate the related features of biological immune system. In order to solve the problems of the ambiguity classification of Chinese words and needs too much manual work always in the traditional ways. The principle of the system in biology is antibody specific recognize the antigen and interact with each other. This article put forward a new model——immune specificity sentiment analysis to calculating the Chinese short tests' emotional polarity which learned from the artificial immune model of limited resources. The model not only can be used for one-time cluster learning, also show the strong ability of continuous learning. It is very suitable for natural language emotional polarity classification. By analyzing the experimental data, we get a more accurately emotional tendency analysis in order to achieve more accurate tendency positioning. KEYWORD: Specific immune recognition; Emotional polarity classification; Antigen; Antibody
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