TEXT SENTIMENT ANALYSIS BASED ON CNNS AND SVM
Journal: INTERNATIONAL JOURNAL OF RESEARCH -GRANTHAALAYAH (Vol.7, No. 6)Publication Date: 2019-06-30
Authors : C. Arunabala P. Jwalitha Soniya Nuthalapati;
Page : 77-83
Keywords : Emotion Analysis; Deep Learning; Convolution Neural Network; SVM.;
Abstract
The traditional text sentiment analysis method is mainly based on machine learning. However, its dependence on emotion dictionary construction and artificial design and extraction features makes the generalization ability limited. In contrast, depth models have more powerful expressive power, and can learn complex mapping functions from data to affective semantics better. In this paper, a Convolution Neural Networks (CNNs) model combined with SVM text sentiment analysis is proposed. The experimental results show that the proposed method improves the accuracy of text sentiment classification effectively compared with traditional CNN, and confirms the effectiveness of sentiment analysis based on CNNs and SVM.
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