基于文本纹理特征的中文情感倾向性分类

Texture Based Sentiment Orientation Identification for Chinese Texts

随着互联网的发展,社交网络、电子商务等已经成为人们关注的焦点,对社交网络的文本进行情感倾向性分析和挖掘变得越来越重要。该文针对网络上的中文文本,提出一种基于文本纹理特征的情感倾向性分类方法。通过测试多种文本纹理特征对文本情感倾向性的影响,成功将文本纹理特征融入情感分类中。通过计算各类特征与文本的情感倾向性的相关度,对特征进行降维。相对于基于词频的情感倾向性分类方法,查准率平均提高了10%左右。

With the development of Internet, the text orientation identification and text mining in social network is becoming a hot research issue. In this paper, a text sentiment orientation identification method using textures is pro posed. The feature reduction is conducted by mutual information between the texture features and the text orienta tions. Compared to sentiment orientation classification method based on word frequency, the proposed method is proved about 10% increase for precision on average.