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Article

Weibo Text Sentiment Analysis Based on BERT and Deep Learning

School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
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Author to whom correspondence should be addressed.
Appl. Sci. 2021, 11(22), 10774; https://doi.org/10.3390/app112210774
Submission received: 9 October 2021 / Revised: 29 October 2021 / Accepted: 8 November 2021 / Published: 15 November 2021
(This article belongs to the Special Issue Application of Artificial Intelligence, Deep Neural Networks)

Abstract

With the rapid increase of public opinion data, the technology of Weibo text sentiment analysis plays a more and more significant role in monitoring network public opinion. Due to the sparseness and high-dimensionality of text data and the complex semantics of natural language, sentiment analysis tasks face tremendous challenges. To solve the above problems, this paper proposes a new model based on BERT and deep learning for Weibo text sentiment analysis. Specifically, first using BERT to represent the text with dynamic word vectors and using the processed sentiment dictionary to enhance the sentiment features of the vectors; then adopting the BiLSTM to extract the contextual features of the text, the processed vector representation is weighted by the attention mechanism. After weighting, using the CNN to extract the important local sentiment features in the text, finally the processed sentiment feature representation is classified. A comparative experiment was conducted on the Weibo text dataset collected during the COVID-19 epidemic; the results showed that the performance of the proposed model was significantly improved compared with other similar models.
Keywords: BERT; sentiment analysis; Weibo text; word vector; deep learning BERT; sentiment analysis; Weibo text; word vector; deep learning

Share and Cite

MDPI and ACS Style

Li, H.; Ma, Y.; Ma, Z.; Zhu, H. Weibo Text Sentiment Analysis Based on BERT and Deep Learning. Appl. Sci. 2021, 11, 10774. https://doi.org/10.3390/app112210774

AMA Style

Li H, Ma Y, Ma Z, Zhu H. Weibo Text Sentiment Analysis Based on BERT and Deep Learning. Applied Sciences. 2021; 11(22):10774. https://doi.org/10.3390/app112210774

Chicago/Turabian Style

Li, Hongchan, Yu Ma, Zishuai Ma, and Haodong Zhu. 2021. "Weibo Text Sentiment Analysis Based on BERT and Deep Learning" Applied Sciences 11, no. 22: 10774. https://doi.org/10.3390/app112210774

APA Style

Li, H., Ma, Y., Ma, Z., & Zhu, H. (2021). Weibo Text Sentiment Analysis Based on BERT and Deep Learning. Applied Sciences, 11(22), 10774. https://doi.org/10.3390/app112210774

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