Who cites Do Kook Choe
- Automatic Sarcasm Detection: A SurveyarXiv:1602.03426Aditya Joshi, Pushpak Bhattacharyya, Mark James Carman2016 · 216 citationsAre Word Embedding-based Features Useful for Sarcasm Detection?Conference on Empirical Methods in Natural Language Processing (EMNLP)Aditya Joshi, Vaibhav Tripathi, Kevin Patel, et al.2016 · 212 citationsTweet Sarcasm Detection Using Deep Neural NetworkInternational Conference on Computational Linguistics (COLING)Meishan Zhang, Yue Zhang, Guohong Fu2016 · 190 citations
- Creating and Characterizing a Diverse Corpus of Sarcasm in DialogueShereen Oraby, Vrindavan Harrison, Lena Reed, et al.2016 · 163 citations
- SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and ArabicIbrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, et al.2022 · 146 citationsSparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and SentimentAnnual Meeting of the Association for Computational Linguistics (ACL)Byron C. Wallace, Do Kook Choe, Eugene Charniak2015 · 123 citationsSarcasm Analysis Using Conversation ContextComputational LinguisticsDebanjan Ghosh, Alexander R. Fabbri, Smaranda Muresan2018 · 119 citationsYour Sentiment Precedes You: Using an author's historical tweets to predict sarcasmWorkshop on Computational Approaches to Subjectivity, Sentiment and Social Media AnalysisAnupam Khattri, Aditya Joshi, Pushpak Bhattacharyya, et al.2015 · 114 citationsA Report on the 2020 Sarcasm Detection Shared TaskWorkshop on Figurative Language ProcessingDebanjan Ghosh, Avijit Vajpayee, Smaranda Muresan2020 · 92 citationsCASCADE: Contextual Sarcasm Detection in Online Discussion ForumsInternational Conference on Computational Linguistics (COLING)Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, et al.2018 · 89 citationsHarnessing Sequence Labeling for Sarcasm Detection in Dialogue from TV Series ‘Friends'Conference on Computational Natural Language Learning (CoNLL)Aditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, et al.2016 · 87 citationsPutting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter ConversationsACL Student Research WorkshopGavin Abercrombie, Dirk Hovy2016 · 85 citationsSarcasm Detection Using an Ensemble ApproachWorkshop on Figurative Language ProcessingJens Lemmens, Ben Burtenshaw, Ehsan Lotfi, et al.2020 · 56 citationsRepresenting Social Media Users for Sarcasm DetectionConference on Empirical Methods in Natural Language Processing (EMNLP)Y. Alex Kolchinski, Christopher Potts2018 · 54 citationsExploring Author Context for Detecting Intended vs Perceived SarcasmAnnual Meeting of the Association for Computational Linguistics (ACL)Silviu Oprea, Walid Magdy2019 · 47 citationsDetecting Sarcasm in Conversation Context Using Transformer-Based ModelsWorkshop on Figurative Language ProcessingAdithya Avvaru, Sanath Vobilisetty, Radhika Mamidi2020 · 46 citationsWLV at SemEval-2018 Task 3: Dissecting Tweets in Search of IronyInternational Workshop on Semantic Evaluation (SemEval)Omid Rohanian, Shiva Taslimipoor, Richard Evans, et al.2018 · 39 citationsC-Net: Contextual Network for Sarcasm DetectionWorkshop on Figurative Language ProcessingAmit Kumar Jena, Aman Sinha, Rohit Agarwal2020 · 38 citations
- Breaking NLP: Using Morphosyntax, Semantics, Pragmatics and World Knowledge to Fool Sentiment Analysis SystemsProceedings of the First Workshop on Building Linguistically Generalizable NLP SystemsTaylor Mahler, Willy Cheung, Micha Elsner, et al.2017 · 34 citationsNeural Sarcasm Detection using Conversation ContextWorkshop on Figurative Language ProcessingNikhil Jaiswal2020 · 32 citationsA deep-learning framework to detect sarcasm targetsConference on Empirical Methods in Natural Language Processing (EMNLP)Jasabanta Patro, Srijan Bansal, Animesh Mukherjee2019 · 29 citationsNLPRL-IITBHU at SemEval-2018 Task 3: Combining Linguistic Features and Emoji pre-trained CNN for Irony Detection in TweetsInternational Workshop on Semantic Evaluation (SemEval)Harsh Rangwani, Devang Kulshreshtha, Anil Kumar Singh2018 · 28 citationsLatent-Optimized Adversarial Neural Transfer for Sarcasm DetectionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xu Guo, Boyang Li, Han Yu, et al.2021 · 27 citations
- A Survey on Automated Sarcasm Detection on TwitterarXiv:2202.02516Bleau Moores, Vijay Mago2022 · 19 citationsThe Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm GenerationFindings of the Association for Computational LinguisticsTyler Loakman, Aaron Maladry, Chenghua Lin2023 · 18 citationsPerceived and Intended Sarcasm Detection with Graph Attention NetworksFindings of the Association for Computational LinguisticsJoan Plepi, Lucie Flek2021 · 18 citationsDoes Commonsense help in detecting Sarcasm?Workshop on Insights from Negative Results in NLPSomnath Basu Roy Chowdhury, Snigdha Chaturvedi2021 · 17 citations
- A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X PerspectivesQingcheng Zeng, An-Ran Li2022 · 14 citationsSarcasm Detection is Way Too Easy! An Empirical Comparison of Human and Machine Sarcasm DetectionFindings of the Association for Computational LinguisticsIbrahim Abu Farha, Steven Wilson, Silviu Oprea, et al.2022 · 13 citationsShould a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Silviu Vlad Oprea, Steven Wilson, Walid Magdy2022 · 13 citationsValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English TweetsInternational Workshop on Semantic Evaluation (SemEval)Delia Irazú Hernández Farías, Viviana Patti, Paolo Rosso2018 · 13 citationsPerceived and Intended Sarcasm Detection with Graph Attention NetworksWorkshop on Noisy User-generated TextJoan Plepi, Lucie Flek2021 · 11 citations
- Interpreting Verbal Irony: Linguistic Strategies and the Connection to the Type of Semantic IncongruityDebanjan Ghosh, Elena Musi, Smaranda Muresan2020 · 10 citations
- How Challenging is Sarcasm versus Irony Classification?: A Study With a Dataset from English LiteratureAditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, et al.2016 · 10 citationsNULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep LearningInternational Workshop on Semantic Evaluation (SemEval)Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy, et al.2022 · 6 citations‘Who would have thought of that!': A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm DetectionWorkshop on Extra-Propositional Aspects of Meaning in Computational LinguisticsAditya Joshi, Prayas Jain, Pushpak Bhattacharyya, et al.2016 · 5 citations
- Computational Sarcasm Analysis on Social Media: A Systematic ReviewarXiv:2209.06170Faria Binte Kader, Nafisa Hossain Nujat, Tasmia Binte Sogir, et al.2022 · 4 citationsI2C at SemEval-2022 Task 6: Intended Sarcasm in English using Deep Learning TechniquesInternational Workshop on Semantic Evaluation (SemEval)Adrián Moreno Monterde, Laura Vázquez Ramos, Jacinto Mata, et al.2022 · 3 citationsR2D2 at SemEval-2022 Task 6: Are language models sarcastic enough? Finetuning pre-trained language models to identify sarcasmInternational Workshop on Semantic Evaluation (SemEval)Mayukh Sharma, Ilanthenral Kandasamy, Vasantha W B2022 · 2 citationsLDR at SemEval-2018 Task 3: A Low Dimensional Text Representation for Irony DetectionInternational Workshop on Semantic Evaluation (SemEval)Bilal Ghanem, Francisco Rangel, Paolo Rosso2018 · 2 citationsJCT at SemEval-2022 Task 6-A: Sarcasm Detection in Tweets Written in English and Arabic using Preprocessing Methods and Word N-gramsInternational Workshop on Semantic Evaluation (SemEval)Yaakov HaCohen-Kerner, Matan Fchima, Ilan Meyrowitsch2022 · 1 citation
- Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language ModelsarXiv:2603.23251Nasser A Alsadhan2026
- Irony Detection in Hebrew Documents: A Novel Dataset and an Evaluation of Neural Classification MethodsAvi Shmidman, Elda Weizman, Avishay Gerczuk2025
- Linguistic Features in Automatic Sarcasm DetectionMartina Ducret, Lauren Kruse, Carlos Martinez, et al.2020
Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)Annual Meeting of the Association for Computational Linguistics (ACL)Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.2019 · 314 citations
A Transformer-based approach to Irony and Sarcasm detectionNeural Computing and ApplicationsRolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis2019 · 312 citations
A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence ClassificationInternational Joint Conference on Natural Language Processing (IJCNLP)Ye Zhang, Byron Wallace2017 · 259 citations
A Large Self-Annotated Corpus for SarcasmLanguage Resources and Evaluation Conference (LREC)Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli2018 · 258 citations
The Importance of Modeling Social Factors of Language: Theory and PracticeConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Dirk Hovy, Diyi Yang2021 · 234 citations
Towards Multimodal Sarcasm Detection (An \textitObviously Perfect Paper)Annual Meeting of the Association for Computational Linguistics (ACL)Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.2019 · 228 citations
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