mlsanityData to 7 Oct 2026

Embarrassingly Simple Unsupervised Aspect Extraction

arXiv 2004.13580 ↗First posted 28 Apr 2020cs.CLcited by 13

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Abstract (arXiv)

We present a simple but effective method for aspect identification in sentiment analysis. Our unsupervised method only requires word embeddings and a POS tagger, and is therefore straightforward to apply to new domains and languages. We introduce Contrastive Attention (CAt), a novel single-head attention mechanism based on an RBF kernel, which gives a considerable boost in performance and makes the model interpretable. Previous work relied on syntactic features and complex neural models. We show that given the simplicity of current benchmark datasets for aspect extraction, such complex models are not needed. The code to reproduce the experiments reported in this paper is available at https://github.com/clips/cat

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2020.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 6; 2024: 2.

13 papers.

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  1. 2022A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challengescited by 61
  2. 2022UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Miningcited by 33
  3. 2024From Facts to Insights: A Study on the Generation and Evaluation of Analytical Reports for Deciphering Earnings Callscited by 6
  4. 2021Hyperbolic Disentangled Representation for Fine-Grained Aspect Extractioncited by 3
  5. 2023Syntax-aware Hybrid prompt model for Few-shot multi-modal sentiment analysiscited by 2
  6. 2023You Are What You Talk About: Inducing Evaluative Topics for Personality Analysiscited by 1
  7. 2023A Weak Supervision Approach for Few-Shot Aspect Based Sentimentcited by 1
  8. 2023Document-Level Supervision for Multi-Aspect Sentiment Analysis Without Fine-grained Labelscited by 1
  9. 2023A Self-enhancement Multitask Framework for Unsupervised Aspect Category Detectioncited by 1
  10. 2021Recommend for a Reason: Unlocking the Power of Unsupervised Aspect-Sentiment Co-Extractioncited by 0
  11. 2022Ensemble Creation via Anchored Regularization for Unsupervised Aspect Extractioncited by 0
  12. 2023From Stars to Insights: Exploration and Implementation of Unified Sentiment Analysis with Distant Supervisioncited by 0
1 more
  1. 2024Embarrassingly Simple Unsupervised Aspect Based Sentiment Tuple Extractioncited by 0