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Emotion Analysis of Industry Research Report Based on the Hybrid Method of BERT and BiLSTM

In: Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022)

Author

Listed:
  • Qi Luo

    (Guizhou University of Finance and Economics, School of Big Data Application and Economics
    Guizhou University of Finance and Economics, Guizhou Institution for Technology Innovation & Entrepreneurship Investment)

  • Mu Zhang

    (Guizhou University of Finance and Economics, School of Big Data Application and Economics)

Abstract

ABSTRACT In this era of information explosion, industry research papers contain a large number of information about the current business situation and profit and loss of enterprises, which reflects the credit risk of enterprises from the side, further affecting the objective evaluation of financial institutions such as banks. In order to improve the accuracy of the emotional analysis of industry research papers, this paper adopts the emotional analysis method based on the combination of BERT and BiLSTM, and selects 100 industry research papers from 38 industries of Dongfang Fortune Network in 2021 as samples for emotional analysis. To better demonstrate the performance of this model, this paper uses the SnowNLP model to compare with it. The results show that the accuracy, recall and F1 values based on the mixed model of BERT and BiLSTM are 85.42%, 82% and 83.68% respectively. The accuracy, recall and F1 value of SnowNLP model are 75%, 78% and 76.47% respectively. It can be concluded that the performance of the method proposed in this paper is good, and it has certain validity for the sentiment analysis of industry research papers, and has certain value in helping to predict the future development trend of the industry.

Suggested Citation

  • Qi Luo & Mu Zhang, 2023. "Emotion Analysis of Industry Research Report Based on the Hybrid Method of BERT and BiLSTM," Advances in Economics, Business and Management Research, in: Sen Qiao & Hongbin Cao & Aiwen Liu & Xueliang Chen & Tiefei Li (ed.), Proceedings of the 10th Annual Meeting of Risk Analysis Council of China Association for Disaster Prevention (RAC 2022), pages 170-176, Springer.
    • Handle: RePEc:spr:advbcp:978-94-6463-194-4_24
    DOI: 10.2991/978-94-6463-194-4_24
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