Computer Engineering and Applications ›› 2018, Vol. 54 ›› Issue (14): 158-162.

### Text sentiment classification based on sentiment series distance and turning assimilation

ZHENG Cheng, TAN Xiaoyu, YU Xiukai, CAO Yang

1. School of Computer Science and Technology, Anhui University, Hefei 230601, China
• Online:2018-07-15 Published:2018-08-06

### 基于情感时序距离和转折同化的文本情感分类

1. 安徽大学 计算机科学与技术学院，合肥 230601

Abstract: Considering the overall texts orientation identification of Chinese emotional texts and their sentiment express sequence have a great connection, and for the emotional texts, emotion tendency expression which is closer to the end of the texts is more influential to identify whole texts orientation. Therefore, for the short texts which express emotion inconspicuously or complicatedly, this paper considers the sequence of the appearance of the emotional nodes in the text and the sentiment assimilation of the turning point to classify the emotional texts more efficiently. The experimental result on the emotional texts dataset crawled from a shopping site shows that the classification method proposed in this paper is significantly better than the support vector machine classifier that is based on word features simply.