A sentiment analysis approach based on exploiting Chinese linguistic features and classification. (2018)

• Record Type: Journal Article
• Authors: Gao, Kai; Su, Shu; Li, Dan-Yang; Zhang, S-S.; Wang, J-S.
• Is Part Of: International journal of modelling, identification and control. Volume 29:Number 3(2018)
• Page Start: 226
• Page End: 232
• Publication Date: 2018
• Subjects: sentiment analysis -- linguistic feature -- SVMperf -- classification; Engineering -- Methodology -- Periodicals; Science -- Methodology -- Periodicals; 001.42
• Languages: English
• ISSNs: 1746-6172

Abstract

This paper proposes a novel approach to exploiting linguistic features and SVM perf algorithm based semantic classification, and this approach is applied into sentiment analysis. It uses the dependency relationship to do the linguistic feature extraction. This paper adopts χ 2 (chi-square) and pointwise mutual information (PMI) metrics for feature selection. Furthermore, as for the approach on sentiment analysis, this paper uses the SVM perf algorithm to implement the alternative structural formulation of the SVM optimisation problem for classification. E-commerce datasets are used to evaluate the experiment performance. Experiment results show the feasibility of the approach. Existing problems and further works are also presented.