# Improving BERT Performance for Aspect-Based Sentiment Analysis

arXiv: https://arxiv.org/abs/2010.11731 · HTML: https://mlsanity.com/paper/2010.11731/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Oct 2020.

## Built on by (most cited first, 15 of 15)

- [A Generative Language Model for Few-shot Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2204.05356/) (2022)
- [BERT-ASC: Auxiliary-Sentence Construction for Implicit Aspect Learning in Sentiment Analysis](https://mlsanity.com/paper/2203.11702/) (2022)
- [A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2306.11260/) (2023)
- [Aspect-Based Sentiment Analysis Techniques: A Comparative Study](https://mlsanity.com/paper/2407.02834/) (2024)
- [UniParma at SemEval-2021 Task 5: Toxic Spans Detection Using CharacterBERT and Bag-of-Words Model](https://mlsanity.com/paper/2103.09645/) (2021)
- [Detecting Conspiracy Theory Against COVID-19 Vaccines](https://mlsanity.com/paper/2211.13003/) (2022)
- [Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviews](https://mlsanity.com/paper/2408.13202/) (2024)
- [Survey of Generative Methods for Social Media Analysis](https://mlsanity.com/paper/2112.07041/) (2021)
- [Human-in-the-Loop Disinformation Detection: Stance, Sentiment, or Something Else?](https://mlsanity.com/paper/2111.05139/) (2021)
- [Relationship of the language distance to English ability of a country](https://mlsanity.com/paper/2211.07855/) (2022)
- [OpinionConv: Conversational Product Search with Grounded Opinions](https://mlsanity.com/paper/2308.04226/) (2023)
- [Linguistic features for sentence difficulty prediction in ABSA](https://mlsanity.com/paper/2402.03163/) (2024)
- [Supervised Gradual Machine Learning for Aspect Category Detection](https://mlsanity.com/paper/2404.05245/) (2024)
- [KPC-cF: Aspect-Based Sentiment Analysis via Implicit-Feature Alignment with Corpus Filtering](https://mlsanity.com/paper/2407.00342/) (2024)
- [Dopamin: Transformer-based Comment Classifiers through Domain Post-Training and Multi-level Layer Aggregation](https://mlsanity.com/paper/2408.04663/) (2024)

## Abstract (arXiv)

Aspect-Based Sentiment Analysis (ABSA) studies the consumer opinion on the market products. It involves examining the type of sentiments as well as sentiment targets expressed in product reviews. Analyzing the language used in a review is a difficult task that requires a deep understanding of the language. In recent years, deep language models, such as BERT citedevlin2019bert, have shown great progress in this regard. In this work, we propose two simple modules called Parallel Aggregation and Hierarchical Aggregation to be utilized on top of BERT for two main ABSA tasks namely Aspect Extraction (AE) and Aspect Sentiment Classification (ASC) in order to improve the model's performance. We show that applying the proposed models eliminates the need for further training of the BERT model. The source code is available on the Web for further research and reproduction of the results.