A sentiment analysis approach based on exploiting Chinese linguistic features and classification
by Kai Gao; Shu Su; Dan-Yang Li; S-S. Zhang; J-S. Wang
International Journal of Modelling, Identification and Control (IJMIC), Vol. 29, No. 3, 2018

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 χ² (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.

Online publication date: Tue, 17-Apr-2018

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