research-article

Shortcut Enhanced Syntactic and Semantic Dual-channel Network for Aspect-based Sentiment Analysis

Authors:

Jiazheng Huang,

Yayun GongAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 11

Article No.: 252, Pages 1 - 20

https://doi.org/10.1145/3629518

Published: 20 November 2023 Publication History

Abstract

Aspect-based sentiment analysis (ABSA) is a fine-grained task that predicts the sentiment polarity of different aspects in the same sentence. The main challenge is how to build a strong dependency between aspects and sentiment. Recently, the graph neural network (GNN) has become the mainstream trend to extract syntactic dependency relations from the syntactic dependency tree. However, further improvements are hampered by the inherent mistake on the syntactic dependency tree. Consequently, this article presents a dual-channel model to investigate whether considering both syntactic dependency and semantic relevance can further improve the performance. Specifically, we propose a multi-head syntactic graph convolution network (MHGCN) module in the syntactic channel, focusing on different aspects of the syntactic flow in parallel. We also design a syntactic local attention mechanism (Syn-LFAM) and a semantic local attention mechanism (Sem-LFAM) to fully exploit the crucial local information, respectively. Moreover, we use the cross semantic-syntax interaction module and gate fusion mechanism to control the combination of semantic and syntax dynamically. The experimental results show that we utilize less resource consumption, and the final model outperforms the state-of-the-art methods on three of the four publicly available datasets.

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Cited By

Xu YZhang YSun YZhou H(2025)An adaptive method for determining the optimal number of topics in topic modelingPeerJ Computer Science10.7717/peerj-cs.272311(e2723)Online publication date: 28-Feb-2025
https://doi.org/10.7717/peerj-cs.2723
Chen XXie HTao XWang FZhang DDai H(2025)A computational analysis of aspect-based sentiment analysis research through bibliometric mapping and topic modelingJournal of Big Data10.1186/s40537-025-01068-y12:1Online publication date: 19-Feb-2025
https://doi.org/10.1186/s40537-025-01068-y
Pokhriyal HJain G(2025)Supposititious Sarcasm Detection and Sentiment Analysis Coping Hindi Language in Social Networks Harnessing Zipf- Mandelbrot Probabilistic Optimisation and Perplexity Entropy LearningACM Transactions on Asian and Low-Resource Language Information Processing10.1145/371206124:2(1-28)Online publication date: 16-Jan-2025
https://dl.acm.org/doi/10.1145/3712061

Index Terms

Shortcut Enhanced Syntactic and Semantic Dual-channel Network for Aspect-based Sentiment Analysis
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Sentiment analysis

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 11

November 2023

255 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3633309

Editor:
Imed Zitouni
Google, USA

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Association for Computing Machinery

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Publication History

Published: 20 November 2023

Online AM: 23 October 2023

Accepted: 11 October 2023

Revised: 12 September 2023

Received: 03 June 2022

Published in TALLIP Volume 22, Issue 11

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Cited By

Xu YZhang YSun YZhou H(2025)An adaptive method for determining the optimal number of topics in topic modelingPeerJ Computer Science10.7717/peerj-cs.272311(e2723)Online publication date: 28-Feb-2025
https://doi.org/10.7717/peerj-cs.2723
Chen XXie HTao XWang FZhang DDai H(2025)A computational analysis of aspect-based sentiment analysis research through bibliometric mapping and topic modelingJournal of Big Data10.1186/s40537-025-01068-y12:1Online publication date: 19-Feb-2025
https://doi.org/10.1186/s40537-025-01068-y
Pokhriyal HJain G(2025)Supposititious Sarcasm Detection and Sentiment Analysis Coping Hindi Language in Social Networks Harnessing Zipf- Mandelbrot Probabilistic Optimisation and Perplexity Entropy LearningACM Transactions on Asian and Low-Resource Language Information Processing10.1145/371206124:2(1-28)Online publication date: 16-Jan-2025
https://dl.acm.org/doi/10.1145/3712061

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