mlsanityData to 7 Oct 2026

Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue

arXiv 1709.05404 ↗First posted 15 Sep 2017cs.CLcited by 42

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Abstract (arXiv)

The use of irony and sarcasm in social media allows us to study them at scale for the first time. However, their diversity has made it difficult to construct a high-quality corpus of sarcasm in dialogue. Here, we describe the process of creating a large- scale, highly-diverse corpus of online debate forums dialogue, and our novel methods for operationalizing classes of sarcasm in the form of rhetorical questions and hyperbole. We show that we can use lexico-syntactic cues to reliably retrieve sarcastic utterances with high accuracy. To demonstrate the properties and quality of our corpus, we conduct supervised learning experiments with simple features, and show that we achieve both higher precision and F than previous work on sarcasm in debate forums dialogue. We apply a weakly-supervised linguistic pattern learner and qualitatively analyze the linguistic differences in each class.

Key facts. Cited by 42 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Sep 2017.

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Citing papers per year: 2021: 6; 2022: 4; 2023: 5; 2024: 9; 2025: 14; 2026: 4.

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  1. 2025Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challengescited by 31
  2. 2022A Multimodal Corpus for Emotion Recognition in Sarcasmcited by 29
  3. 2024SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understandingcited by 20
  4. 2024Stress-Testing Long-Context Language Models with Lifelong ICL and Task Haystackcited by 19
  5. 2021A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflictcited by 14
  6. 2021Latent-Optimized Adversarial Neural Transfer for Sarcasm Detectioncited by 6
  7. 2024Systematic Literature Review: Computational Approaches for Humour Style Classificationcited by 6
  8. 2021"Laughing at you or with you": The Role of Sarcasm in Shaping the Disagreement Spacecited by 5
  9. 2021Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversationscited by 5
  10. 2024Generalizable Sarcasm Detection Is Just Around The Corner, Of Course!cited by 5
  11. 2025Irony Detection, Reasoning and Understanding in Zero-shot Learningcited by 5
  12. 2025Emotion-o1: Adaptive Long Reasoning for Emotion Understanding in LLMscited by 5
30 more
  1. 2025CAF-I: A Collaborative Multi-Agent Framework for Enhanced Irony Detection with Large Language Modelscited by 4
  2. 2022A Survey on Automated Sarcasm Detection on Twittercited by 3
  3. 2023The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languagescited by 3
  4. 2022Computational Sarcasm Analysis on Social Media: A Systematic Reviewcited by 2
  5. 2023BNS-Net: A Dual-channel Sarcasm Detection Method Considering Behavior-level and Sentence-level Conflictscited by 2
  6. 2024KoCoSa: Korean Context-aware Sarcasm Detection Datasetcited by 2
  7. 2024Revealing the impact of synthetic native samples and multi-tasking strategies in Hindi-English code-mixed humour and sarcasm detectioncited by 2
  8. 2025Optimism, Expectation, or Sarcasm? Multi-Class Hope Speech Detection in Spanish and Englishcited by 2
  9. 2025SEVADE: Self-Evolving Multi-Agent Analysis with Decoupled Evaluation for Hallucination-Resistant Irony Detectioncited by 2
  10. 2025World model inspired sarcasm reasoning with large language model agentscited by 2
  11. 2021Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literaturecited by 1
  12. 2022Contrastive Learning of Sociopragmatic Meaning in Social Mediacited by 1
  13. 2023Multi-Task Learning Improves Performance In Deep Argument Mining Modelscited by 1
  14. 2023Sarcasm Detection in a Disaster Contextcited by 1
  15. 2025Intermediate-Task Transfer Learning: Leveraging Sarcasm Detection for Stance Detectioncited by 1
  16. 2025Sarcasm Detection as a Catalyst: Improving Stance Detection with Cross-Target Capabilitiescited by 1
  17. 2025A Transformer and Prototype-based Interpretable Model for Contextual Sarcasm Detectioncited by 1
  18. 2025Class Distillation with Mahalanobis Contrast: An Efficient Training Paradigm for Pragmatic Language Understanding Taskscited by 1
  19. 2026RAM-SD: Retrieval-Augmented Multi-agent framework for Sarcasm Detectioncited by 1
  20. 2026Indirect Question Answering in English, German and Bavarian: A Challenging Task for High- and Low-Resource Languages Alikecited by 1
  21. 2021Interpretable Multi-Head Self-Attention model for Sarcasm Detection in social mediacited by 0
  22. 2023Researchers eye-view of sarcasm detection in social media textual contentcited by 0
  23. 2024When Do "More Contexts" Help with Sarcasm Recognition?cited by 0
  24. 2024Figuratively Speaking: Authorship Attribution via Multi-Task Figurative Language Modelingcited by 0
  25. 2024Was that Sarcasm?: A Literature Survey on Sarcasm Detectioncited by 0
  26. 2025MuSaRoNews: A Multidomain, Multimodal Satire Dataset from Romanian News Articlescited by 0
  27. 2025PromptAug: Fine-grained Conflict Classification Using Data Augmentationcited by 0
  28. 2025Transfer Learning via Lexical Relatedness: A Sarcasm and Hate Speech Case Studycited by 0
  29. 2026Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steeringcited by 0
  30. 2026When Benchmarks Mislead: Shortcut Learning, Length Confounds, and the Limits of Cross-Dataset Generalization in Multilingual Fake News and Sarcasm Detectioncited by 0