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Aspect Extraction

Aspect extraction is the task of identifying and extracting terms relevant for opinion mining and sentiment analysis, for example terms for product attributes or features.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 21–30 of 92 papers

Title	Date	Tasks	Status	Hype	Score
Does local pruning offer task-specific models to learn effectively ?	Sep 1, 2021	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5
A Wide Evaluation of ChatGPT on Affective Computing Tasks	Aug 26, 2023	Aspect ExtractionSarcasm Detection	CodeCode Available	0	5
Double Embeddings and CNN-based Sequence Labeling for Aspect Extraction	May 11, 2018	Aspect-Based Sentiment Analysis (ABSA)Aspect Extraction	CodeCode Available	0	5
An Unsupervised Neural Attention Model for Aspect Extraction	Jul 1, 2017	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5
Hyperbolic Disentangled Representation for Fine-Grained Aspect Extraction	Dec 16, 2021	Aspect Extraction	CodeCode Available	0	5
Automatic Aspect Extraction from Scientific Texts	Oct 6, 2023	Aspect Extraction	CodeCode Available	0	5
Aspect Detection using Word and Char Embeddings with (Bi)LSTM and CRF	Sep 3, 2019	Aspect ExtractionWord Embeddings	CodeCode Available	0	5
An Aspect Extraction Framework using Different Embedding Types, Learning Models, and Dependency Structure	Mar 5, 2025	Aspect-Based Sentiment AnalysisAspect Extraction	CodeCode Available	0	5
Multilingual aspect clustering for sentiment analysis	Dec 9, 2019	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5
Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches	Nov 8, 2023	Aspect-Based Sentiment AnalysisAspect-Based Sentiment Analysis (ABSA)	CodeCode Available	0	5

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All datasets SemEval-2014 Task-4 SemEval 2015 Task 12 SemEval 2014 Task 4 Sub Task 1 SemEval 2016 Task 5 Sub Task 1 Slot 2 YASO - YELP

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	InstructABSA	Laptop (F1)	92.3	—	Unverified
2	ACE	Laptop (F1)	87.4	—	Unverified
3	PH-SUM	Laptop (F1)	86.09	—	Unverified
4	BAT	Laptop (F1)	85.57	—	Unverified
5	DE-CNN	Restaurant (F1)	85.2	—	Unverified
6	Wei et al. (2020)	Laptop (F1)	82.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ACE	Restaurant (F1)	80.3	—	Unverified
2	Wei et al. (2020)	Restaurant (F1)	72.7	—	Unverified
3	DE-CNN	Restaurant (F1)	68.28	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DE-CNN	Laptop (F1)	81.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DE-CNN	Restaurant (F1)	74.37	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	RACL - Laptops	F1	23	—	Unverified