Journal
KNOWLEDGE-BASED SYSTEMS
Volume 236, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.knosys.2021.107736
Keywords
Aspect-based Sentiment Analysis; Phrase dependency graph; Relational graph attention network
Categories
Funding
- National Key Research and Development Program of China [2019YFB1406300]
- National Natural Science Foundation of China [61972336, 62073284]
- Zhejiang Provincial Natural Science Foundation of China [LY22F020027, LY19F030008]
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Aspect-based Sentiment Analysis (ABSA) is a method that aims to identify the sentiment polarity of specific aspects in a sentence. This paper proposes a phrase dependency graph attention network (PD-RGAT) based on a relational graph constructed from the phrase dependency graph, and experimental results demonstrate its effectiveness.
Aspect-based Sentiment Analysis (ABSA) is a subclass of sentiment analysis, which aims to identify the sentiment polarity such as positive, negative, or neutral for specific aspects or attributes that appear in a sentence. Previous studies have focused on extracting aspect-sentiment polarity pairs based on dependency trees, ignoring edge labels and phrase information. In this paper, we instead propose a phrase dependency graph attention network (PD-RGAT) on the ABSA task, which is a relational graph attention network constructed based on the phrase dependency graph, aggregating directed dependency edges and phrase information. We perform experiments with two pre-training models, GloVe and BERT. Experimental results on the benchmarking datasets (i.e., Twitter, Restaurant, and Laptop) demonstrate that our proposed PD-RGAT has comparable effectiveness to a range of state-of-the-art models and further illustrate that the graph convolutional structure based on the phrase dependency graph can capture both syntactic information and short long-range word dependencies. It also shows that incorporating directed edge labels and phrase information can enhance the capture of aspect-sentiment polarities on the ABSA task. (C) 2021 Elsevier B.V. All rights reserved.
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