# Learning Implicit Sentiment in Aspect-based Sentiment Analysis with Supervised Contrastive Pre-Training

arXiv: https://arxiv.org/abs/2111.02194 · HTML: https://mlsanity.com/paper/2111.02194/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 38 references that are in the map.
- First posted on arXiv 3 Nov 2021.

## Builds on (most cited first, 19 of 19)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Momentum Contrast for Unsupervised Visual Representation Learning](https://mlsanity.com/paper/1911.05722/) (2019)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Supervised Contrastive Learning](https://mlsanity.com/paper/2004.11362/) (2020)
- [How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings](https://mlsanity.com/paper/1909.00512/) (2019)
- [Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filtering](https://mlsanity.com/paper/1602.01585/) (2016)
- [BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis](https://mlsanity.com/paper/1904.02232/) (2019)
- [Relational Graph Attention Network for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2004.12362/) (2020)
- [Interactive Attention Networks for Aspect-Level Sentiment Classification](https://mlsanity.com/paper/1709.00893/) (2017)
- [Aspect Level Sentiment Classification with Deep Memory Network](https://mlsanity.com/paper/1605.08900/) (2016)
- [Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification](https://mlsanity.com/paper/1908.11860/) (2019)
- [SKEP: Sentiment Knowledge Enhanced Pre-training for Sentiment Analysis](https://mlsanity.com/paper/2005.05635/) (2020)
- [Attentional Encoder Network for Targeted Sentiment Classification](https://mlsanity.com/paper/1902.09314/) (2019)
- [Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa](https://mlsanity.com/paper/2104.04986/) (2021)
- [Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/1603.06679/) (2016)
- [Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2009.07964/) (2020)

## Built on by (most cited first, 30 of 37)

- [Sentiment Analysis in the Era of Large Language Models: A Reality Check](https://mlsanity.com/paper/2305.15005/) (2023)
- [Is ChatGPT a Good Sentiment Analyzer? A Preliminary Study](https://mlsanity.com/paper/2304.04339/) (2023)
- [Reasoning Implicit Sentiment with Chain-of-Thought Prompting](https://mlsanity.com/paper/2305.11255/) (2023)
- [DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis](https://mlsanity.com/paper/2211.05705/) (2022)
- [Causal Intervention Improves Implicit Sentiment Analysis](https://mlsanity.com/paper/2208.09329/) (2022)
- [Generative Aspect-Based Sentiment Analysis with Contrastive Learning and Expressive Structure](https://mlsanity.com/paper/2211.07743/) (2022)
- [RVISA: Reasoning and Verification for Implicit Sentiment Analysis](https://mlsanity.com/paper/2407.02340/) (2024)
- [A Multi-level Supervised Contrastive Learning Framework for Low-Resource Natural Language Inference](https://mlsanity.com/paper/2205.15550/) (2022)
- [Aspect-Based Sentiment Analysis with Explicit Sentiment Augmentations](https://mlsanity.com/paper/2312.10961/) (2023)
- [Towards Robust ESG Analysis Against Greenwashing Risks: Aspect-Action Analysis with Cross-Category Generalization](https://mlsanity.com/paper/2502.15821/) (2025)
- [Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis](https://mlsanity.com/paper/2210.09803/) (2022)
- [PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2208.01368/) (2022)
- [EduRABSA: An Education Review Dataset for Aspect-based Sentiment Analysis Tasks](https://mlsanity.com/paper/2508.17008/) (2025)
- [My Words Imply Your Opinion: Reader Agent-based Propagation Enhancement for Personalized Implicit Emotion Analysis](https://mlsanity.com/paper/2412.07367/) (2024)
- [Causal Prompting for Implicit Sentiment Analysis with Large Language Models](https://mlsanity.com/paper/2507.00389/) (2025)
- [CONTRASTE: Supervised Contrastive Pre-training With Aspect-based Prompts For Aspect Sentiment Triplet Extraction](https://mlsanity.com/paper/2310.15577/) (2023)
- [SentiCSE: A Sentiment-aware Contrastive Sentence Embedding Framework with Sentiment-guided Textual Similarity](https://mlsanity.com/paper/2404.01104/) (2024)
- [Large Language Models in Targeted Sentiment Analysis](https://mlsanity.com/paper/2404.12342/) (2024)
- [ImpScore: A Learnable Metric For Quantifying The Implicitness Level of Sentence](https://mlsanity.com/paper/2411.05172/) (2024)
- [Reassessing the Role of Chain-of-Thought in Sentiment Analysis: Insights and Limitations](https://mlsanity.com/paper/2501.08641/) (2025)
- [A Dual-Contrastive Framework for Low-Resource Cross-Lingual Named Entity Recognition](https://mlsanity.com/paper/2204.00796/) (2022)
- [Fast Few shot Self-attentive Semi-supervised Political Inclination Prediction](https://mlsanity.com/paper/2209.10292/) (2022)
- [ECQED: Emotion-Cause Quadruple Extraction in Dialogs](https://mlsanity.com/paper/2306.03969/) (2023)
- [Towards Robust Aspect-based Sentiment Analysis through Non-counterfactual Augmentations](https://mlsanity.com/paper/2306.13971/) (2023)
- [ATESA-BAERT: A Heterogeneous Ensemble Learning Model for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2307.15920/) (2023)
- [Interpretation modeling: Social grounding of sentences by reasoning over their implicit moral judgments](https://mlsanity.com/paper/2312.03726/) (2023)
- [Exploring ChatGPT-based Augmentation Strategies for Contrastive Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2409.11218/) (2024)
- [When LLMs Team Up: The Emergence of Collaborative Affective Computing](https://mlsanity.com/paper/2506.01698/) (2025)
- [Application of Multiple Chain-of-Thought in Contrastive Reasoning for Implicit Sentiment Analysis](https://mlsanity.com/paper/2503.07140/) (2025)
- [CHEER-Ekman: Fine-grained Embodied Emotion Classification](https://mlsanity.com/paper/2506.01047/) (2025)

## Abstract (arXiv)

Aspect-based sentiment analysis aims to identify the sentiment polarity of a specific aspect in product reviews. We notice that about 30% of reviews do not contain obvious opinion words, but still convey clear human-aware sentiment orientation, which is known as implicit sentiment. However, recent neural network-based approaches paid little attention to implicit sentiment entailed in the reviews. To overcome this issue, we adopt Supervised Contrastive Pre-training on large-scale sentiment-annotated corpora retrieved from in-domain language resources. By aligning the representation of implicit sentiment expressions to those with the same sentiment label, the pre-training process leads to better capture of both implicit and explicit sentiment orientation towards aspects in reviews. Experimental results show that our method achieves state-of-the-art performance on SemEval2014 benchmarks, and comprehensive analysis validates its effectiveness on learning implicit sentiment.