mlsanityData to 14 Oct 2026

"When Words Fail, Emojis Prevail": Generating Sarcastic Utterances with Emoji Using Valence Reversal and Semantic Incongruity

arXiv 2305.04105 ↗First posted 6 May 2023cs.CLcited by 1

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Abstract (arXiv)

Sarcasm is a form of figurative language that serves as a humorous tool for mockery and ridicule. We present a novel architecture for sarcasm generation with emoji from a non-sarcastic input sentence in English. We divide the generation task into two sub tasks: one for generating textual sarcasm and another for collecting emojis associated with those sarcastic sentences. Two key elements of sarcasm are incorporated into the textual sarcasm generation task: valence reversal and semantic incongruity with context, where the context may involve shared commonsense or general knowledge between the speaker and their audience. The majority of existing sarcasm generation works have focused on this textual form. However, in the real world, when written texts fall short of effectively capturing the emotional cues of spoken and face-to-face communication, people often opt for emojis to accurately express their emotions. Due to the wide range of applications of emojis, incorporating appropriate emojis to generate textual sarcastic sentences helps advance sarcasm generation. We conclude our study by evaluating the generated sarcastic sentences using human judgement. All the codes and data used in this study has been made publicly available.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 28 of its 97 references that are in the map. First posted on arXiv 6 May 2023.

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28 of 97 references.

References · 28

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2015Distilling the Knowledge in a Neural Networkcited by 10,324
  4. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,682
  5. 2021Symbolic Knowledge Distillation: from General Language Models to Commonsense Modelscited by 270
  6. 2017OpenNMT: Open-source Toolkit for Neural Machine Translationcited by 251
  7. 2017Using millions of emoji occurrences to learn any-domain representations for detecting sentiment, emotion and sarcasmcited by 118
  8. 2017A Large Self-Annotated Corpus for Sarcasmcited by 64
  9. 2018Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approachcited by 55
  10. 2016Detecting Sarcasm in Multimodal Social Platformscited by 44
  11. 2018Reasoning with Sarcasm by Reading In-betweencited by 38
  12. 2016A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networkscited by 33
16 more
  1. 2020R3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledgecited by 32
  2. 2019A Transformer-based approach to Irony and Sarcasm detectioncited by 28
  3. 2016Modelling Context with User Embeddings for Sarcasm Detection in Social Mediacited by 26
  4. 2018CASCADE: Contextual Sarcasm Detection in Online Discussion Forumscited by 26
  5. 2019Sentiment and Sarcasm Classification with Multitask Learningcited by 19
  6. 2018Deep contextualized word representations for detecting sarcasm and ironycited by 18
  7. 2018Sarcasm Analysis using Conversation Contextcited by 17
  8. 2016Are Word Embedding-based Features Useful for Sarcasm Detection?cited by 14
  9. 2020Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Mediacited by 8
  10. 2017Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialogcited by 7
  11. 2020Sarcasm Detection using Context Separators in Online Discoursecited by 7
  12. 2020Augmenting Data for Sarcasm Detection with Unlabeled Conversation Contextcited by 6
  13. 2020Reactive Supervision: A New Method for Collecting Sarcasm Datacited by 4
  14. 2018NTUA-SLP at SemEval-2018 Task 2: Predicting Emojis using RNNs with Context-aware Attentioncited by 2
  15. 2021A Robust Deep Ensemble Classifier for Figurative Language Detectioncited by 2
  16. 2022How to Describe Images in a More Funny Way? Towards a Modular Approach to Cross-Modal Sarcasm Generationcited by 1

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