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Aspect-Based Sentiment Analysis using Local Context Focus Mechanism with DeBERTa

arXiv 2207.02424 ↗First posted 6 Jul 2022cs.CL cs.IRcited by 0

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Abstract (arXiv)

Text sentiment analysis, also known as opinion mining, is research on the calculation of people's views, evaluations, attitude and emotions expressed by entities. Text sentiment analysis can be divided into text-level sentiment analysis, sen-tence-level sentiment analysis and aspect-level sentiment analysis. Aspect-Based Sentiment Analysis (ABSA) is a fine-grained task in the field of sentiment analysis, which aims to predict the polarity of aspects. The research of pre-training neural model has significantly improved the performance of many natural language processing tasks. In recent years, pre training model (PTM) has been applied in ABSA. Therefore, there has been a question, which is whether PTMs contain sufficient syntactic information for ABSA. In this paper, we explored the recent DeBERTa model (Decoding-enhanced BERT with disentangled attention) to solve Aspect-Based Sentiment Analysis problem. DeBERTa is a kind of neural language model based on transformer, which uses self-supervised learning to pre-train on a large number of original text corpora. Based on the Local Context Focus (LCF) mechanism, by integrating DeBERTa model, we purpose a multi-task learning model for aspect-based sentiment analysis. The experiments result on the most commonly used the laptop and restaurant datasets of SemEval-2014 and the ACL twitter dataset show that LCF mechanism with DeBERTa has significant improvement.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 19 of its 62 references that are in the map. First posted on arXiv 6 Jul 2022.

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19 of 62 references.

References · 19

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7 more
  1. 2018Aspect Based Sentiment Analysis with Gated Convolutional Networkscited by 65
  2. 2019Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classificationcited by 62
  3. 2019Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networkscited by 62
  4. 2019Exploiting BERT for End-to-End Aspect-based Sentiment Analysiscited by 57
  5. 2022Scientific and Technological Information Oriented Semantics-adversarial and Media-adversarial Cross-media Retrievalcited by 33
  6. 2019Deep Collaborative Filtering with Multi-Aspect Information in Heterogeneous Networkscited by 27
  7. 2017Learning to Attend via Word-Aspect Associative Fusion for Aspect-based Sentiment Analysiscited by 14

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