English Text Sentiment Analysis Based on Convolutional Neural Network and U-network

Abstract

English text sentiment orientation analysis is a fundamental problem in the field of natural language processing. The traditional word segmentation method can produce ambiguity when dealing with English text. Therefore, this paper proposes a novel English text sentiment analysis based on convolutional neural network and U-network. The proposed method uses a parallel convolution layer to learn the associations and combinations between word vectors. The results are then input into the hierarchical attention network whose basic unit is U-network to determine the affective tendency. The experimental results show that the accuracy of bias classification on the English review dataset reaches 93.45%. Compared with many existing sentiment analysis models, it has more accuracy.