Aspect-Based Sentiment Analysis
152 papers with code • 1 benchmarks • 2 datasets
Benchmarks
These leaderboards are used to track progress in Aspect-Based Sentiment Analysis
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
Libraries
Use these libraries to find Aspect-Based Sentiment Analysis models and implementations
SemEval-2014 Task-4
FABSA
Most implemented papers
Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence
HSLCY/ABSA-BERT-pair
•
•
NAACL 2019
Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity towards a specific aspect, is a challenging subtask of sentiment analysis (SA).
Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis
In this paper, we introduce a new subtask under ABSA, named aspect sentiment triplet extraction (ASTE).
A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction
Aspect-based sentiment analysis (ABSA) task is a multi-grained task of natural language processing and consists of two subtasks: aspect term extraction (ATE) and aspect polarity classification (APC).
A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task
l294265421/ASOTE
•
•
Aspect Sentiment Triplet Extraction (ASTE) aims to extract aspect term, sentiment and opinion term triplets from sentences and tries to provide a complete solution for aspect-based sentiment analysis (ABSA).
Adversarial Training for Aspect-Based Sentiment Analysis with BERT
IMPLabUniPr/Adversarial-Training-for-ABSA
•
•
In this work, we apply adversarial training, which was put forward by Goodfellow et al. (2014), to the post-trained BERT (BERT-PT) language model proposed by Xu et al. (2019) on the two major tasks of Aspect Extraction and Aspect Sentiment Classification in sentiment analysis.
An Unsupervised Neural Attention Model for Aspect Extraction
Unlike topic models which typically assume independently generated words, word embedding models encourage words that appear in similar contexts to be located close to each other in the embedding space.
An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
Aspect-based sentiment analysis produces a list of aspect terms and their corresponding sentiments for a natural language sentence.
Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification
deepopinion/domain-adapted-atsc
•
•
LREC 2020
Aspect-Target Sentiment Classification (ATSC) is a subtask of Aspect-Based Sentiment Analysis (ABSA), which has many applications e. g. in e-commerce, where data and insights from reviews can be leveraged to create value for businesses and customers.
Generalizing Natural Language Analysis through Span-relation Representations
Natural language processing covers a wide variety of tasks predicting syntax, semantics, and information content, and usually each type of output is generated with specially designed architectures.
Toward Tag-free Aspect Based Sentiment Analysis: A Multiple Attention Network Approach
qiangyao1988/Toward-tag-free-ABSA
•
•
Existing aspect based sentiment analysis (ABSA) approaches leverage various neural network models to extract the aspect sentiments via learning aspect-specific feature representations.
