mlsanityData to 14 Oct 2026

Challenges for Open-domain Targeted Sentiment Analysis

arXiv 2204.06893 ↗First posted 14 Apr 2022cs.CLcited by 9

Not on the map. Why?

Abstract (arXiv)

Since previous studies on open-domain targeted sentiment analysis are limited in dataset domain variety and sentence level, we propose a novel dataset consisting of 6,013 human-labeled data to extend the data domains in topics of interest and document level. Furthermore, we offer a nested target annotation schema to extract the complete sentiment information in documents, boosting the practicality and effectiveness of open-domain targeted sentiment analysis. Moreover, we leverage the pre-trained model BART in a sequence-to-sequence generation method for the task. Benchmark results show that there exists large room for improvement of open-domain targeted sentiment analysis. Meanwhile, experiments have shown that challenges remain in the effective use of open-domain data, long documents, the complexity of target structure, and domain variances.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 17 of its 48 references that are in the map. First posted on arXiv 14 Apr 2022.

Builds on

17 of 48 references.

References · 17

  1. 2017Attention Is All You Needcited by 60,361
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  4. 2020Multilingual Denoising Pre-training for Neural Machine Translationcited by 1,035
  5. 2015Order Matters: Sequence to sequence for setscited by 237
  6. 2021A Unified Generative Framework for Aspect-Based Sentiment Analysiscited by 97
  7. 2019Exploiting BERT for End-to-End Aspect-based Sentiment Analysiscited by 57
  8. 2018A Unified Model for Opinion Target Extraction and Target Sentiment Predictioncited by 56
  9. 2019Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classificationcited by 50
  10. 2016SentiHood: Targeted Aspect Based Sentiment Analysis Dataset for Urban Neighbourhoodscited by 32
  11. 2021Solving Aspect Category Sentiment Analysis as a Text Generation Taskcited by 21
  12. 2020GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysiscited by 12
5 more
  1. 2017Lifelong Learning CRF for Supervised Aspect Extractioncited by 9
  2. 2020YASO: A Targeted Sentiment Analysis Evaluation Dataset for Open-Domain Reviewscited by 7
  3. 2019Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learningcited by 4
  4. 2021Towards Target-dependent Sentiment Classification in News Articlescited by 3
  5. 2020Jointly Modeling Aspect and Sentiment with Dynamic Heterogeneous Graph Neural Networkscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 3; 2025: 1; 2026: 1.

9 papers.

  1. 2023Is ChatGPT a Good Sentiment Analyzer? A Preliminary Studycited by 96
  2. 2024Both Matter: Enhancing the Emotional Intelligence of Large Language Models without Compromising the General Intelligencecited by 11
  3. 2023Entity-Level Sentiment Analysis (ELSA): An exploratory task surveycited by 5
  4. 2022Cross-domain Generalization for AMR Parsingcited by 2
  5. 2024A Multilingual Similarity Dataset for News Article Framecited by 2
  6. 2023XAL: EXplainable Active Learning Makes Classifiers Better Low-resource Learnerscited by 1
  7. 2024FaiMA: Feature-aware In-context Learning for Multi-domain Aspect-based Sentiment Analysiscited by 1
  8. 2025EmoGRACE: Aspect-based emotion analysis for social media datacited by 1
  9. 2026DanceHA: A Multi-Agent Framework for Document-Level Aspect-Based Sentiment Analysiscited by 0