mlsanityData to 14 Oct 2026

Author's Sentiment Prediction

arXiv 2011.06128 ↗First posted 12 Nov 2020cs.CL cs.LGcited by 18

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Abstract (arXiv)

We introduce PerSenT, a dataset of crowd-sourced annotations of the sentiment expressed by the authors towards the main entities in news articles. The dataset also includes paragraph-level sentiment annotations to provide more fine-grained supervision for the task. Our benchmarks of multiple strong baselines show that this is a difficult classification task. The results also suggest that simply fine-tuning document-level representations from BERT isn't adequate for this task. Making paragraph-level decisions and aggregating them over the entire document is also ineffective. We present empirical and qualitative analyses that illustrate the specific challenges posed by this dataset. We release this dataset with 5.3k documents and 38k paragraphs covering 3.2k unique entities as a challenge in entity sentiment analysis.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Nov 2020.

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Citing papers per year: 2021: 2; 2022: 5; 2023: 4; 2024: 3; 2025: 4.

18 papers.

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  1. 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
  2. 2023Analyzing Dataset Annotation Quality Management in the Wildcited by 41
  3. 2021TellMeWhy: A Dataset for Answering Why-Questions in Narrativescited by 27
  4. 2023Prompting with Pseudo-Code Instructionscited by 14
  5. 2024CaT-BENCH: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Planscited by 11
  6. 2023Massively Multilingual Corpus of Sentiment Datasets and Multi-faceted Sentiment Classification Benchmarkcited by 10
  7. 2025Benchmarking LLMs for Political Science: A United Nations Perspectivecited by 10
  8. 2024Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategiescited by 8
  9. 2022A Generative Language Model for Few-shot Aspect-Based Sentiment Analysiscited by 7
  10. 2023From Big to Small Without Losing It All: Text Augmentation with ChatGPT for Efficient Sentiment Analysiscited by 6
  11. 2025Entity Framing and Role Portrayal in the Newscited by 6
  12. 2022POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Eventscited by 5
6 more
  1. 2021On Positivity Bias in Negative Reviewscited by 3
  2. 2022Assessment of Massively Multilingual Sentiment Classifierscited by 3
  3. 2022SuMe: A Dataset Towards Summarizing Biomedical Mechanismscited by 2
  4. 2024Entity-Level Sentiment: More than the Sum of Its Partscited by 1
  5. 2025Incentivizing High-Quality Human Annotations with Golden Questionscited by 0
  6. 2025Users as Annotators: LLM Preference Learning from Comparison Modecited by 0