---
title: "Who cites Do Kook Choe — 87 papers of our library"
description: "87 papers of the Elamur Research library cite the works of Do Kook Choe, found in their bibliographies; the most cited first."
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---
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# Who cites Do Kook Choe

100 citations of their works from 87 papers of our library (of the 141,840 whose bibliographies we read) · 50 with a page here, the most cited first · [← Do Kook Choe](https://md.research.elamur.ai/free/en/authors/do-kook-choe/)

1. **[Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 314 citations*
2. **[A Transformer-based approach to Irony and Sarcasm detection](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/) [Neural Computing and Applications](https://md.research.elamur.ai/free/en/venues/neural-computing-and-applications/)**Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis*2019 · 312 citations*
3. **[A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification](https://md.research.elamur.ai/free/en/papers/zhang-2017-sensitivity-analysis-practitioners-guide-convolutional/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Ye Zhang, Byron Wallace*2017 · 259 citations*
4. **[A Large Self-Annotated Corpus for Sarcasm](https://md.research.elamur.ai/free/en/papers/khodak-2018-large-self-annotated-corpus-sarcasm/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli*2018 · 258 citations*
5. **[The Importance of Modeling Social Factors of Language: Theory and Practice](https://md.research.elamur.ai/free/en/papers/hovy-2021-importance-modeling-social-factors-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dirk Hovy, Diyi Yang*2021 · 234 citations*
6. **[Towards Multimodal Sarcasm Detection (An \textitObviously Perfect Paper)](https://md.research.elamur.ai/free/en/papers/castro-2019-multimodal-sarcasm-detection-textitobviously-perfect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 228 citations*
7. [**Automatic Sarcasm Detection: A Survey arXiv:1602.03426**Aditya Joshi, Pushpak Bhattacharyya, Mark James Carman*2016 · 216 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2016-automatic-sarcasm-detection-survey/)
8. **[Are Word Embedding-based Features Useful for Sarcasm Detection?](https://md.research.elamur.ai/free/en/papers/joshi-2016-are-word-embedding-based-features/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aditya Joshi, Vaibhav Tripathi, Kevin Patel, et al.*2016 · 212 citations*
9. **[Tweet Sarcasm Detection Using Deep Neural Network](https://md.research.elamur.ai/free/en/papers/zhang-2016-tweet-sarcasm-detection-deep-neural/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Meishan Zhang, Yue Zhang, Guohong Fu*2016 · 190 citations*
10. [**Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue**Shereen Oraby, Vrindavan Harrison, Lena Reed, et al.*2016 · 163 citations*](https://md.research.elamur.ai/free/en/papers/oraby-2016-creating-characterizing-diverse-corpus-sarcasm/)
11. [**SemEval-2022 Task 6: iSarcasmEval, Intended Sarcasm Detection in English and Arabic**Ibrahim Abu Farha, Silviu Vlad Oprea, Steven Wilson, et al.*2022 · 146 citations*](https://md.research.elamur.ai/free/en/papers/farha-2022-semeval-2022-task-6-isarcasmeval/)
12. **[Sparse, Contextually Informed Models for Irony Detection: Exploiting User Communities, Entities and Sentiment](https://md.research.elamur.ai/free/en/papers/wallace-2015-sparse-contextually-informed-models-irony/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Byron C. Wallace, Do Kook Choe, Eugene Charniak*2015 · 123 citations*
13. **[Sarcasm Analysis Using Conversation Context](https://md.research.elamur.ai/free/en/papers/ghosh-2018-sarcasm-analysis-conversation-context/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Debanjan Ghosh, Alexander R. Fabbri, Smaranda Muresan*2018 · 119 citations*
14. **[Your Sentiment Precedes You: Using an author's historical tweets to predict sarcasm](https://md.research.elamur.ai/free/en/papers/khattri-2015-your-sentiment-precedes-you-author/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Anupam Khattri, Aditya Joshi, Pushpak Bhattacharyya, et al.*2015 · 114 citations*
15. **[A Report on the 2020 Sarcasm Detection Shared Task](https://md.research.elamur.ai/free/en/papers/ghosh-2020-report-2020-sarcasm-detection-shared/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan*2020 · 92 citations*
16. **[CASCADE: Contextual Sarcasm Detection in Online Discussion Forums](https://md.research.elamur.ai/free/en/papers/hazarika-2018-cascade-contextual-sarcasm-detection-online/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, et al.*2018 · 89 citations*
17. **[Harnessing Sequence Labeling for Sarcasm Detection in Dialogue from TV Series ‘Friends'](https://md.research.elamur.ai/free/en/papers/joshi-2016-harnessing-sequence-labeling-sarcasm-detection/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Aditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, et al.*2016 · 87 citations*
18. **[Putting Sarcasm Detection into Context: The Effects of Class Imbalance and Manual Labelling on Supervised Machine Classification of Twitter Conversations](https://md.research.elamur.ai/free/en/papers/abercrombie-2016-putting-sarcasm-detection-into-context/) [ACL Student Research Workshop](https://md.research.elamur.ai/free/en/venues/acl-student-research-workshop/)**Gavin Abercrombie, Dirk Hovy*2016 · 85 citations*
19. **[Sarcasm Detection Using an Ensemble Approach](https://md.research.elamur.ai/free/en/papers/lemmens-2020-sarcasm-detection-ensemble-approach/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Jens Lemmens, Ben Burtenshaw, Ehsan Lotfi, et al.*2020 · 56 citations*
20. **[Representing Social Media Users for Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/kolchinski-2018-representing-social-media-users-sarcasm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Y. Alex Kolchinski, Christopher Potts*2018 · 54 citations*
21. **[Exploring Author Context for Detecting Intended vs Perceived Sarcasm](https://md.research.elamur.ai/free/en/papers/oprea-2019-exploring-author-context-detecting-intended/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Silviu Oprea, Walid Magdy*2019 · 47 citations*
22. **[Detecting Sarcasm in Conversation Context Using Transformer-Based Models](https://md.research.elamur.ai/free/en/papers/avvaru-2020-detecting-sarcasm-conversation-context-transformer/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Adithya Avvaru, Sanath Vobilisetty, Radhika Mamidi*2020 · 46 citations*
23. **[WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony](https://md.research.elamur.ai/free/en/papers/rohanian-2018-wlv-semeval-2018-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Omid Rohanian, Shiva Taslimipoor, Richard Evans, et al.*2018 · 39 citations*
24. **[C-Net: Contextual Network for Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/jena-2020-c-net-contextual-network-sarcasm/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Amit Kumar Jena, Aman Sinha, Rohit Agarwal*2020 · 38 citations*
25. [**Breaking NLP: Using Morphosyntax, Semantics, Pragmatics and World Knowledge to Fool Sentiment Analysis Systems Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems**Taylor Mahler, Willy Cheung, Micha Elsner, et al.*2017 · 34 citations*](https://md.research.elamur.ai/free/en/papers/mahler-2017-breaking-nlp-morphosyntax-semantics-pragmatics/)
26. **[Neural Sarcasm Detection using Conversation Context](https://md.research.elamur.ai/free/en/papers/jaiswal-2020-neural-sarcasm-detection-conversation-context/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Nikhil Jaiswal*2020 · 32 citations*
27. **[A deep-learning framework to detect sarcasm targets](https://md.research.elamur.ai/free/en/papers/patro-2019-deep-learning-framework-detect-sarcasm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jasabanta Patro, Srijan Bansal, Animesh Mukherjee*2019 · 29 citations*
28. **[NLPRL-IITBHU at SemEval-2018 Task 3: Combining Linguistic Features and Emoji pre-trained CNN for Irony Detection in Tweets](https://md.research.elamur.ai/free/en/papers/rangwani-2018-nlprl-iitbhu-semeval-2018-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Harsh Rangwani, Devang Kulshreshtha, Anil Kumar Singh*2018 · 28 citations*
29. **[Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/guo-2021-latent-optimized-adversarial-neural-transfer/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xu Guo, Boyang Li, Han Yu, et al.*2021 · 27 citations*
30. [**A Survey on Automated Sarcasm Detection on Twitter arXiv:2202.02516**Bleau Moores, Vijay Mago*2022 · 19 citations*](https://md.research.elamur.ai/free/en/papers/moores-2022-survey-automated-sarcasm-detection-twitter/)
31. **[The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation](https://md.research.elamur.ai/free/en/papers/loakman-2023-iron-ic-melting-pot-reviewing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tyler Loakman, Aaron Maladry, Chenghua Lin*2023 · 18 citations*
32. **[Perceived and Intended Sarcasm Detection with Graph Attention Networks](https://md.research.elamur.ai/free/en/papers/plepi-2021-perceived-intended-sarcasm-detection-graph-2021-findings-emnlp-408/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joan Plepi, Lucie Flek*2021 · 18 citations*
33. **[Does Commonsense help in detecting Sarcasm?](https://md.research.elamur.ai/free/en/papers/chowdhury-2021-does-commonsense-help-detecting-sarcasm/) [Workshop on Insights from Negative Results in NLP](https://md.research.elamur.ai/free/en/venues/insights/)**Somnath Basu Roy Chowdhury, Snigdha Chaturvedi*2021 · 17 citations*
34. [**A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives**Qingcheng Zeng, An-Ran Li*2022 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-survey-automatic-irony-processing-linguistic/)
35. **[Sarcasm Detection is Way Too Easy! An Empirical Comparison of Human and Machine Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/farha-2022-sarcasm-detection-is-way-too/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ibrahim Abu Farha, Steven Wilson, Silviu Oprea, et al.*2022 · 13 citations*
36. **[Should a Chatbot be Sarcastic? Understanding User Preferences Towards Sarcasm Generation](https://md.research.elamur.ai/free/en/papers/oprea-2022-should-chatbot-be-sarcastic-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Silviu Vlad Oprea, Steven Wilson, Walid Magdy*2022 · 13 citations*
37. **[ValenTO at SemEval-2018 Task 3: Exploring the Role of Affective Content for Detecting Irony in English Tweets](https://md.research.elamur.ai/free/en/papers/farias-2018-valento-semeval-2018-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Delia Irazú Hernández Farías, Viviana Patti, Paolo Rosso*2018 · 13 citations*
38. **[Perceived and Intended Sarcasm Detection with Graph Attention Networks](https://md.research.elamur.ai/free/en/papers/plepi-2021-perceived-intended-sarcasm-detection-graph/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Joan Plepi, Lucie Flek*2021 · 11 citations*
39. [**Interpreting Verbal Irony: Linguistic Strategies and the Connection to the Type of Semantic Incongruity**Debanjan Ghosh, Elena Musi, Smaranda Muresan*2020 · 10 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2020-interpreting-verbal-irony-linguistic-strategies/)
40. [**How Challenging is Sarcasm versus Irony Classification?: A Study With a Dataset from English Literature**Aditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, et al.*2016 · 10 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2016-how-challenging-is-sarcasm-versus/)
41. **[NULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep Learning](https://md.research.elamur.ai/free/en/papers/rahgouy-2022-null-semeval-2022-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy, et al.*2022 · 6 citations*
42. **[‘Who would have thought of that!': A Hierarchical Topic Model for Extraction of Sarcasm-prevalent Topics and Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/joshi-2016-who-would-have-thought-that/) [Workshop on Extra-Propositional Aspects of Meaning in Computational Linguistics](https://md.research.elamur.ai/free/en/venues/workshop-on-extra-propositional-aspects-of-meaning-in-computational-linguistics/)**Aditya Joshi, Prayas Jain, Pushpak Bhattacharyya, et al.*2016 · 5 citations*
43. [**Computational Sarcasm Analysis on Social Media: A Systematic Review arXiv:2209.06170**Faria Binte Kader, Nafisa Hossain Nujat, Tasmia Binte Sogir, et al.*2022 · 4 citations*](https://md.research.elamur.ai/free/en/papers/kader-2022-computational-sarcasm-analysis-social-media/)
44. **[I2C at SemEval-2022 Task 6: Intended Sarcasm in English using Deep Learning Techniques](https://md.research.elamur.ai/free/en/papers/monterde-2022-i2c-semeval-2022-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Adrián Moreno Monterde, Laura Vázquez Ramos, Jacinto Mata, et al.*2022 · 3 citations*
45. **[R2D2 at SemEval-2022 Task 6: Are language models sarcastic enough? Finetuning pre-trained language models to identify sarcasm](https://md.research.elamur.ai/free/en/papers/sharma-2022-r2d2-semeval-2022-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Mayukh Sharma, Ilanthenral Kandasamy, Vasantha W B*2022 · 2 citations*
46. **[LDR at SemEval-2018 Task 3: A Low Dimensional Text Representation for Irony Detection](https://md.research.elamur.ai/free/en/papers/ghanem-2018-ldr-semeval-2018-task-3/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Bilal Ghanem, Francisco Rangel, Paolo Rosso*2018 · 2 citations*
47. **[JCT at SemEval-2022 Task 6-A: Sarcasm Detection in Tweets Written in English and Arabic using Preprocessing Methods and Word N-grams](https://md.research.elamur.ai/free/en/papers/kerner-2022-jct-semeval-2022-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Yaakov HaCohen-Kerner, Matan Fchima, Ilan Meyrowitsch*2022 · 1 citation*
48. [**Is AI Catching Up to Human Expression? Exploring Emotion, Personality, Authorship, and Linguistic Style in English and Arabic with Six Large Language Models arXiv:2603.23251**Nasser A Alsadhan*2026*](https://md.research.elamur.ai/free/en/papers/alsadhan-2026-ai-catching-up-human-expression/)
49. [**Irony Detection in Hebrew Documents: A Novel Dataset and an Evaluation of Neural Classification Methods**Avi Shmidman, Elda Weizman, Avishay Gerczuk*2025*](https://md.research.elamur.ai/free/en/papers/shmidman-2025-irony-detection-hebrew-documents-novel/)
50. [**Linguistic Features in Automatic Sarcasm Detection**Martina Ducret, Lauren Kruse, Carlos Martinez, et al.*2020*](https://md.research.elamur.ai/free/en/papers/ducret-2020-linguistic-features-automatic-sarcasm-detection/)

37 more citing papers of our library have no page here yet.

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