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A new method of emotional analysis based on CNN–BiLSTM hybrid neural network

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Abstract

The hybrid neural network model proposed in this paper consists of two main parts: extracting local features of text vectors by convolutional neural network, extracting global features related to text context by BiLSTM, and fusing the features extracted by the two complementary models. In this paper, the pre-processed sentences are put into the hybrid neural network for training. The trained hybrid neural network can automatically classify the sentences. When testing the algorithm proposed in this paper, the training corpus is Word2vec. The test results show that the accuracy rate of text categorization reaches 94.2%, and the number of iterations is 10. The results show that the proposed algorithm has high accuracy and good robustness when the sample size is seriously unbalanced.

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Funding

This research work is supported by Intelligent Psychological Consultation System Based on NLP and User Portraits (201910060022), College Students’ Innovative Entrepreneurial Training Plan Program (National Program, 2019.6-2020.6), National Natural Science Foundation of China (Grant No. 61571328), Tianjin Key Natural Science Foundation (No. 13JCZDJC34600), CSC Foundation (No. 201308120010), Major projects of science and technology in Tianjin (No. 15ZXDSGX 00050), Training plan of Tianjin University Innovation Team (No. TD12-5016, No.TD13- 5025), Major projects of science and technology for their services in Tianjin (Nos. 16ZXFWGX00010, 17YFZC GX00360), the Key Subject Foundation of Tianjin (15JCYB JC46500), Training plan of Tianjin 131 Innovation Talent Team (No. TD2015-23).

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Authors and Affiliations

  1. Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin, 300384, China

    Zi-xian Liu, De-gan Zhang, Gu-zhao Luo, Ming Lian & Bing Liu

  2. Tianjin Key Lab of Intelligent Computing & Novel software Technology, Tianjin University of Technology, Tianjin, 300384, China

    Zi-xian Liu, De-gan Zhang, Gu-zhao Luo, Ming Lian & Bing Liu

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  1. Zi-xian Liu
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  4. Ming Lian
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Correspondence to Zi-xian Liu.

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Author Liu Zi-xian, Zhang De-gan, Luo Gu-zhao, Lian Ming and Liu Bing declare that they have no conflict of interest.

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De-gan Zhang, Gu-zhao Luo and Ming Lian are co-first author.

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Liu, Zx., Zhang, Dg., Luo, Gz. et al. A new method of emotional analysis based on CNN–BiLSTM hybrid neural network. Cluster Comput 23, 2901–2913 (2020). https://doi.org/10.1007/s10586-020-03055-9

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