mlsanityData to 14 Oct 2026

Improving Language Models for Emotion Analysis: Insights from Cognitive Science

arXiv 2406.10265 ↗First posted 11 Jun 2024cs.CL cs.AIcited by 4

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Abstract (arXiv)

We propose leveraging cognitive science research on emotions and communication to improve language models for emotion analysis. First, we present the main emotion theories in psychology and cognitive science. Then, we introduce the main methods of emotion annotation in natural language processing and their connections to psychological theories. We also present the two main types of analyses of emotional communication in cognitive pragmatics. Finally, based on the cognitive science research presented, we propose directions for improving language models for emotion analysis. We suggest that these research efforts pave the way for constructing new annotation schemes, methods, and a possible benchmark for emotional understanding, considering different facets of human emotion and communication.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 37 of its 112 references that are in the map. First posted on arXiv 11 Jun 2024.

Builds on

37 of 112 references.

References · 37

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  4. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  5. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  6. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  7. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  8. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 1,011
  9. 2020GoEmotions: A Dataset of Fine-Grained Emotionscited by 486
  10. 2023Toxicity in ChatGPT: Analyzing Persona-assigned Language Modelscited by 360
  11. 2023A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesiscited by 353
  12. 2023Large Language Models Fail on Trivial Alterations to Theory-of-Mind Taskscited by 292
25 more
  1. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 268
  2. 2023Understanding Social Reasoning in Language Models with Language Modelscited by 172
  3. 2023FANToM: A Benchmark for Stress-testing Machine Theory of Mind in Interactionscited by 171
  4. 2023ExpertPrompting: Instructing Large Language Models to be Distinguished Expertscited by 142
  5. 2024Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignmentcited by 104
  6. 2023Answering Questions by Meta-Reasoning over Multiple Chains of Thoughtcited by 87
  7. 2022EmoBank: Studying the Impact of Annotation Perspective and Representation Format on Dimensional Emotion Analysiscited by 76
  8. 2023How FaR Are Large Language Models From Agents with Theory-of-Mind?cited by 76
  9. 2020Beneath the Tip of the Iceberg: Current Challenges and New Directions in Sentiment Analysis Researchcited by 67
  10. 2022Do Large Language Models know what humans know?cited by 60
  11. 2022Dimensional Modeling of Emotions in Text with Appraisal Theories: Corpus Creation, Annotation Reliability, and Predictioncited by 46
  12. 2019GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perceptioncited by 37
  13. 2020Appraisal Theories for Emotion Classification in Textcited by 28
  14. 2022Mind the gap: Challenges of deep learning approaches to Theory of Mindcited by 21
  15. 2023Does ChatGPT have Theory of Mind?cited by 16
  16. 2021Emotion Recognition under Consideration of the Emotion Component Process Modelcited by 12
  17. 2019An Analysis of Emotion Communication Channels in Fan Fiction: Towards Emotional Storytellingcited by 9
  18. 2020Towards Label-Agnostic Emotion Embeddingscited by 9
  19. 2023Emotion Recognition based on Psychological Components in Guided Narratives for Emotion Regulationcited by 7
  20. 2023Where are We in Event-centric Emotion Analysis? Bridging Emotion Role Labeling and Appraisal-based Approachescited by 7
  21. 2020Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?cited by 5
  22. 2022Experiencer-Specific Emotion and Appraisal Predictioncited by 4
  23. 2022Natural Language Processing for Cognitive Analysis of Emotionscited by 3
  24. 2024Sequence-to-Sequence Language Models for Character and Emotion Detection in Dream Narrativescited by 3
  25. 2024Can AI and humans genuinely communicate?cited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 2; 2026: 2.

4 papers.

  1. 2025Analysing Moral Bias in Finetuned LLMs through Mechanistic Interpretabilitycited by 2
  2. 2026CAREBench: Evaluating LLMs' Emotion Understanding by Assessing Cognitive Appraisal Reasoningcited by 2
  3. 2025Formalizing Style in Personal Narrativescited by 0
  4. 2026NTDH: Complex Reasoning for Comprehensive Affective Analysiscited by 0