Abstract: Combined with TF-IDF method and variance statistical forumla, a new method for the extraction of multi-class feature is presented. This microblog short text oriented extraction method is used to determine the fine-grained sentiment type. Then the processes of fine-grained sentiment analysis is bulit. This method is used to praticipate the NLP&CC2013 evaluation, and the effectiveness of this method is proved by the good ranking of the subimitted data.

Key words: natural language processing, text sentiment analysis, fine-grained sentiment analysis, multi-class feature extraction

摘要： 结合TF-IDF方法与方差统计方法, 提出一种实现多分类特征抽取的计算方法。采用先极性判断, 后细粒度情感判断的处理方法, 构建细粒度情感分析与判断流程, 并将其应用于微博短文本的细粒度情感判断。通过NLP&CC2013评测所提供的训练语料对该方法有效性进行验证, 结果表明该方法具有较好的抽取效果。

关键词: 自然语言处理, 文本情感分析, 细粒度情感, 多分类特征抽取