A sentiment analysis approach based on exploiting Chinese linguistic features and classification

摘要

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.