mlsanityData to 7 Oct 2026

Researchers eye-view of sarcasm detection in social media textual content

arXiv 2304.08582 ↗First posted 17 Apr 2023cs.CLcited by 0

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Abstract (arXiv)

The enormous use of sarcastic text in all forms of communication in social media will have a physiological effect on target users. Each user has a different approach to misusing and recognising sarcasm. Sarcasm detection is difficult even for users, and this will depend on many things such as perspective, context, special symbols. So, that will be a challenging task for machines to differentiate sarcastic sentences from non-sarcastic sentences. There are no exact rules based on which model will accurately detect sarcasm from many text corpus in the current situation. So, one needs to focus on optimistic and forthcoming approaches in the sarcasm detection domain. This paper discusses various sarcasm detection techniques and concludes with some approaches, related datasets with optimal features, and the researcher's challenges.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 64 references that are in the map. First posted on arXiv 17 Apr 2023.

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References · 16

  1. 2019Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)cited by 173
  2. 2017Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasmcited by 117
  3. 2017A Large Self-Annotated Corpus for Sarcasmcited by 63
  4. 2017Creating and Characterizing a Diverse Corpus of Sarcasm in Dialoguecited by 42
  5. 2019iSarcasm: A Dataset of Intended Sarcasmcited by 39
  6. 2018Reasoning with Sarcasm by Reading In-betweencited by 38
  7. 2019A Transformer-based approach to Irony and Sarcasm detectioncited by 28
  8. 2016Modelling Context with User Embeddings for Sarcasm Detection in Social Mediacited by 26
  9. 2019Sentiment and Sarcasm Classification with Multitask Learningcited by 19
  10. 2017Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translationcited by 18
  11. 2018Deep contextualized word representations for detecting sarcasm and ironycited by 18
  12. 2017Harnessing Cognitive Features for Sarcasm Detectioncited by 8
4 more
  1. 2020Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Mediacited by 8
  2. 2020Sarcasm Detection in Tweets with BERT and GloVe Embeddingscited by 8
  3. 2020Sarcasm Detection using Context Separators in Online Discoursecited by 7
  4. 2020Augmenting Data for Sarcasm Detection with Unlabeled Conversation Contextcited by 6

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