Sentiment analysis of Chinese poetry incorporating imagery features

Yong Lu; Anke Li; Jiayun Li

doi:10.1117/12.3034754

11 July 2024 Sentiment analysis of Chinese poetry incorporating imagery features

Yong Lu, Anke Li, Jiayun Li

Proceedings Volume 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024); 132101T (2024) https://doi.org/10.1117/12.3034754
Event: Third International Symposium on Computer Applications and Information Systems (ISCAIS 2023), 2024, Wuhan, China

Abstract

Classical Chinese poetry employs poetic imagery extensively to convey feelings. To improve the effect of poetry sentiment analysis, this paper introduces imagery features into the model and proposes an improved BiLSTM poetry sentiment analysis model. The experimental results demonstrate that the improved BiLSTM model incorporating imagery features achieves better results than the traditional BiLSTM model in the task of poetry sentiment analysis.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yong Lu, Anke Li, and Jiayun Li "Sentiment analysis of Chinese poetry incorporating imagery features", Proc. SPIE 13210, Third International Symposium on Computer Applications and Information Systems (ISCAIS 2024), 132101T (11 July 2024); https://doi.org/10.1117/12.3034754

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