mlsanityData to 14 Oct 2026

Was that Sarcasm?: A Literature Survey on Sarcasm Detection

arXiv 2412.00425 ↗First posted 30 Nov 2024cs.CLcited by 0

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Abstract (arXiv)

Sarcasm is hard to interpret as human beings. Being able to interpret sarcasm is often termed as a sign of intelligence, given the complex nature of sarcasm. Hence, this is a field of Natural Language Processing which is still complex for computers to decipher. This Literature Survey delves into different aspects of sarcasm detection, to create an understanding of the underlying problems faced during detection, approaches used to solve this problem, and different forms of available datasets for sarcasm detection.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 11 of its 25 references that are in the map. First posted on arXiv 30 Nov 2024.

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References · 11

  1. 2015Show, Attend and Tell: Neural Image Caption Generation with Visual Attentioncited by 1,423
  2. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,067
  3. 2019Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)cited by 174
  4. 2022FLUTE: Figurative Language Understanding through Textual Explanationscited by 79
  5. 2017A Large Self-Annotated Corpus for Sarcasmcited by 64
  6. 2017Creating and Characterizing a Diverse Corpus of Sarcasm in Dialoguecited by 43
  7. 2018Reasoning with Sarcasm by Reading In-betweencited by 38
  8. 2017Argument Strength is in the Eye of the Beholder: Audience Effects in Persuasioncited by 35
  9. 2022When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialoguescited by 33
  10. 2019A Transformer-based approach to Irony and Sarcasm detectioncited by 28
  11. 2022News Headlines Dataset For Sarcasm Detectioncited by 4

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