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Learning from word semantics to sentence syntax by graph convolutional networks for aspect-based sentiment analysis

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Abstract

Fine-grained sentiment analysis is currently a main focus in the field of natural language processing. In line with the significance of the semantics and the syntax, both semantic- and syntactic-based approaches are dedicatedly devised and developed. However, the highly integrating of the semantic and syntactic information is still challenging, which leads to the misinterpretation of the sentence. In this work, we propose a human cognition-based method for aspect-based sentiment analysis (ABSA), which establishes the learning from word semantics to sentence syntax. A dual-channel semantic learning graph convolutional networks (GCNs) is devised to capture both the general semantics and the structural semantics of words. Subsequently, a syntactic GCN for sentence syntactic structure learning is carried out. As such, the understanding of the given sentence is performed in line with the human processing practice. Our model is evaluated on five public datasets on the tasks of ABSA. Experimental results reveal that the proposed model is a competitive alternative comparing to the state-of-the-arts methods.

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Notes

  1. The source code is accessible below: https://github.com/snowblue2/DSS-GCN.

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Acknowledgements

This work was supported by the National Statistical Science Research Project of China under Grant No. 2016LY98, the Characteristic Innovation Projects of Guangdong Colleges and Universities (Nos. 2018KTSCX049) and the Science and Technology Plan Project of Guangzhou under Grant Nos. 202102080258 and 201903010013.

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Authors and Affiliations

  1. School of Physics and Telecommunication Engineering, South China Normal University, Guangzhou, China

    Anan Dai, Xiaohui Hu & Jinpeng Chen

  2. Department of Computer Science and Operations Research, University of Montreal, Montreal, Canada

    Jianyun Nie

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  1. Anan Dai
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  2. Xiaohui Hu
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  3. Jianyun Nie
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  4. Jinpeng Chen
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Correspondence to Anan Dai or Xiaohui Hu.

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Dai, A., Hu, X., Nie, J. et al. Learning from word semantics to sentence syntax by graph convolutional networks for aspect-based sentiment analysis. Int J Data Sci Anal 14, 17–26 (2022). https://doi.org/10.1007/s41060-022-00315-2

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  • DOI: https://doi.org/10.1007/s41060-022-00315-2

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