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Mining Educational Value of Visualization of Sentiment Classification in Ancient Chinese Literature: From the Perspective of Deep Learning

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  • Jianhong Jia

    (Hunan Railway Professional Technology College, China)

Abstract

This research used deep learning technology to conduct sentiment classification on ancient Chinese literary works and presents the results through visualization. The study collected texts from multiple periods and genres and constructed a deep learning model. The overall accuracy of sentiment classification of the model reached 85%. It has its own advantages and disadvantages in classifying works from different genres and dynasties, and there are multiple factors leading to misjudgments. A combination of multiple tools was adopted for visualization. According to user feedback, the system has value in academic research and visualization display but needs to be optimized. This research provides new methods for the study of ancient literature, etc. In the future, the system will be continuously improved upon, and external integration will be strengthened.

Suggested Citation

  • Jianhong Jia, 2025. "Mining Educational Value of Visualization of Sentiment Classification in Ancient Chinese Literature: From the Perspective of Deep Learning," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 20(1), pages 1-23, January.
    • Handle: RePEc:igg:jwltt0:v:20:y:2025:i:1:p:1-23
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    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWLTT.385603
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    References listed on IDEAS

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    1. Jingsheng Wang & Siyuan Hu & Naeem Jan, 2022. "Research on the Construction of Intelligent Media Ideological and Political Learning Platform Based on Artificial Intelligence Technology," Journal of Mathematics, Hindawi, vol. 2022, pages 1-11, January.
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