Dual-Attention Model for Aspect-Level Sentiment Classification

• URL: http://arxiv.org/abs/2303.07689v1
• Date: Tue, 14 Mar 2023 08:04:38 GMT
• Title: Dual-Attention Model for Aspect-Level Sentiment Classification
• Authors: Mengfei Ye
• Abstract summary: I propose a novel dual-attention model(DAM) for aspect-level sentiment classification. We evaluate the proposed approach on three datasets: laptop and restaurant are from SemEval 2014, and the last one is a twitter dataset.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: I propose a novel dual-attention model(DAM) for aspect-level sentiment classification. Many methods have been proposed, such as support vector machines for artificial design features, long short-term memory networks based on attention mechanisms, and graph neural networks based on dependency parsing. While these methods all have decent performance, I think they all miss one important piece of syntactic information: dependency labels. Based on this idea, this paper proposes a model using dependency labels for the attention mechanism to do this task. We evaluate the proposed approach on three datasets: laptop and restaurant are from SemEval 2014, and the last one is a twitter dataset. Experimental results show that the dual attention model has good performance on all three datasets.

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