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Chinese text sentiment analysis based on fuzzy semantic model

Many recent studies of sentiment analysis have shown that a polarity lexicon can effectively improve the classification results. Social media and Social networks, spontaneously user generated content have become important materials for tracking people's opinions and sentiments online. The mathematical models of fuzzy semantics have provided a formal explanation for the fuzzy nature of human language processing. In this paper we investigate the limitations of traditional sentiment analysis approaches and proposed a better Chinese sentiment analysis approach based on fuzzy semantic model. By using the emotion degree lexicon and fuzzy semantic model, this new approach obtains significant improvement in Chinese text sentiment analysis.