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Identifying implicit emotions via hierarchical structure and rhetorical correlation

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Abstract

Implicit emotional expressions, without using explicit emotion words, usually depend on rhetorics to vividly show the user’s emotions. Sentences carved with specific rhetorics tend to express certain types of emotions. Moreover, a hierarchical structure between emotional pleasure valences and categories exists in psychological sciences from coarse to fine, which helps human understand textual emotions. However, existing implicit emotion identification models ignore the hierarchy structure and the correlations between emotions and rhetorics. In this paper, we propose an implicit emotion identification model via hierarchical structure and rhetorical correlation, which consists of two major layers. Specifically, a hierarchical layer is designed to leverage hierarchical structure and provide coarse-grained emotional valences for identifying emotions, and a correlation layer to learn the latent correlation between emotions and rhetorics. Finally, supported by two layers, a novel multi-task learning model is proposed to train three related identification tasks of pleasure valences, emotions and rhetorics simultaneously, thus improving the overall performance of the emotion identification problem. Experimental results on the implicit emotion dataset demonstrate that the proposed model achieves 89.78% and 88.74% in terms of micro-F1 and weight-F1 metric respectively, outperforming the state-of-the-art methods consistently.

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Acknowledgements

The authors would like to thank all anonymous reviewers for their valuable comments and suggestions which have significantly improved the quality and presentation of this paper. The works described in this paper are supported by the National Natural Science Foundation of China (No.62076158, 62106130, 62072294), the Fundamental Research Program of Shanxi Province (No.202103021223267, 20210302124084), the Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi (No.2021L297, 2021L284), the Taiyuan University of Science and Technology Scientific Reasearch Initial Funding (No.20212053, 20222107).

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Authors and Affiliations

  1. School of Computer Science and Technology, Taiyuan University of Science and Technology, Taiyuan, China

    Xin Chen & Jianghui Cai

  2. School of Computer and Information Technology, Shanxi University, Taiyuan, China

    Suge Wang & Deyu Li

  3. Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan, China

    Suge Wang & Deyu Li

  4. Institute for Infocomm Research, A*STAR, Singapore, Singapore

    Xiaoli Li

  5. R &D Center Machine Intelligence Technology Alibaba DAMO Academy, Singapore, Singapore

    Zhen Hai

  6. School of Finance, Shanxi University of Finance and Economics, Taiyuan, China

    Yang Li

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  1. Xin Chen
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  2. Suge Wang
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  3. Xiaoli Li
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  4. Zhen Hai
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  5. Yang Li
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  6. Deyu Li
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  7. Jianghui Cai
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Correspondence to Suge Wang.

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Chen, X., Wang, S., Li, X. et al. Identifying implicit emotions via hierarchical structure and rhetorical correlation. Int. J. Mach. Learn. & Cyber. 14, 3753–3764 (2023). https://doi.org/10.1007/s13042-023-01862-1

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  • DOI: https://doi.org/10.1007/s13042-023-01862-1

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