Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification

Xiaochen Hou, Jing Huang, Guangtao Wang, Peng Qi, Xiaodong He, Bowen Zhou


Abstract
Recent work on aspect-level sentiment classification has employed Graph Convolutional Networks (GCN) over dependency trees to learn interactions between aspect terms and opinion words. In some cases, the corresponding opinion words for an aspect term cannot be reached within two hops on dependency trees, which requires more GCN layers to model. However, GCNs often achieve the best performance with two layers, and deeper GCNs do not bring any additional gain. Therefore, we design a novel selective attention based GCN model. On one hand, the proposed model enables the direct interaction between aspect terms and context words via the self-attention operation without the distance limitation on dependency trees. On the other hand, a top-k selection procedure is designed to locate opinion words by selecting k context words with the highest attention scores. We conduct experiments on several commonly used benchmark datasets and the results show that our proposed SA-GCN outperforms strong baseline models.
Anthology ID:
2021.textgraphs-1.8
Volume:
Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15)
Month:
June
Year:
2021
Address:
Mexico City, Mexico
Editors:
Alexander Panchenko, Fragkiskos D. Malliaros, Varvara Logacheva, Abhik Jana, Dmitry Ustalov, Peter Jansen
Venue:
TextGraphs
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
83–93
Language:
URL:
https://aclanthology.org/2021.textgraphs-1.8
DOI:
10.18653/v1/2021.textgraphs-1.8
Bibkey:
Cite (ACL):
Xiaochen Hou, Jing Huang, Guangtao Wang, Peng Qi, Xiaodong He, and Bowen Zhou. 2021. Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification. In Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-15), pages 83–93, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Selective Attention Based Graph Convolutional Networks for Aspect-Level Sentiment Classification (Hou et al., TextGraphs 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.textgraphs-1.8.pdf