mlsanityData to 7 Oct 2026

Aspect-Based Sentiment Analysis Techniques: A Comparative Study

arXiv 2407.02834 ↗First posted 3 Jul 2024cs.CLcited by 3

Not on the map. Why?

Abstract (arXiv)

Since the dawn of the digitalisation era, customer feedback and online reviews are unequivocally major sources of insights for businesses. Consequently, conducting comparative analyses of such sources has become the de facto modus operandi of any business that wishes to give itself a competitive edge over its peers and improve customer loyalty. Sentiment analysis is one such method instrumental in gauging public interest, exposing market trends, and analysing competitors. While traditional sentiment analysis focuses on overall sentiment, as the needs advance with time, it has become important to explore public opinions and sentiments on various specific subjects, products and services mentioned in the reviews on a finer-granular level. To this end, Aspect-based Sentiment Analysis (ABSA), supported by advances in Artificial Intelligence (AI) techniques which have contributed to a paradigm shift from simple word-level analysis to tone and context-aware analyses, focuses on identifying specific aspects within the text and determining the sentiment associated with each aspect. In this study, we compare several deep-NN methods for ABSA on two benchmark datasets (Restaurant14 and Laptop-14) and found that FAST LSA obtains the best overall results of 87.6% and 82.6% accuracy but does not pass LSA+DeBERTa which reports 90.33% and 86.21% accuracy respectively.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 30 of its 43 references that are in the map. First posted on arXiv 3 Jul 2024.

Builds on

30 of 43 references.

References · 30

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  4. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  5. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,049
  6. 2019DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lightercited by 4,243
  7. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  8. 2019XLNet: Generalized Autoregressive Pretraining for Language Understandingcited by 2,801
  9. 2019ALBERT: A Lite BERT for Self-supervised Learning of Language Representationscited by 2,772
  10. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,157
  11. 2020MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformerscited by 1,414
  12. 2019TinyBERT: Distilling BERT for Natural Language Understandingcited by 1,153
18 more
  1. 2017SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluationcited by 998
  2. 2020MPNet: Masked and Permuted Pre-training for Language Understandingcited by 973
  3. 2023Instruction Tuning with GPT-4cited by 676
  4. 2020Language-agnostic BERT Sentence Embeddingcited by 621
  5. 2021Sentence-T5: Scalable Sentence Encoders from Pre-trained Text-to-Text Modelscited by 462
  6. 2020SPECTER: Document-level Representation Learning using Citation-informed Transformerscited by 426
  7. 2022Efficient Few-Shot Learning Without Promptscited by 135
  8. 2019Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classificationcited by 62
  9. 2021Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTacited by 41
  10. 2020Adversarial Training for Aspect-Based Sentiment Analysis with BERTcited by 26
  11. 2019A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extractioncited by 18
  12. 2020Improving BERT Performance for Aspect-Based Sentiment Analysiscited by 15
  13. 2021Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Networkcited by 11
  14. 2021LSA: Modeling Aspect Sentiment Coherency via Local Sentiment Aggregationcited by 7
  15. 2022Towards Unifying the Label Space for Aspect- and Sentence-based Sentiment Analysiscited by 6
  16. 2020Rule-Based Approach for Party-Based Sentiment Analysis in Legal Opinion Textscited by 4
  17. 2022PyABSA: A Modularized Framework for Reproducible Aspect-based Sentiment Analysiscited by 4
  18. 2020SigmaLaw-ABSA: Dataset for Aspect-Based Sentiment Analysis in Legal Opinion Textscited by 3

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.

  1. 2024Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviewscited by 2
  2. 2025GeeSanBhava: Sentiment Tagged Sinhala Music Video Comment Data Setcited by 1
  3. 2026SentimentLens: Reconciling Sentiment and Ratings via Dual-Modality in the Hospitality Sectorcited by 0