---
title: "Who cites Sarcasm as Contrast between a Positive Sentiment…"
description: "165 papers of the Elamur Research library cite «Sarcasm as Contrast between a Positive Sentiment and Negative Situation», found in their bibliographies…"
canonical: "https://research.elamur.ai/free/en/papers/riloff-2013-sarcasm-as-contrast-between-positive/cited-by/"
---
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# Who cites «Sarcasm as Contrast between a Positive Sentiment and Negative Situation»

165 papers of our library cite it (of the 140,884 whose bibliographies we read) · 67 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/riloff-2013-sarcasm-as-contrast-between-positive/)

1. [**A Survey on Hate Speech Detection using Natural Language Processing**Anna Schmidt, Michael Wiegand*2017 · 1,799 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2017-survey-hate-speech-detection-natural/)
2. [**SemEval-2018 Task 3: Irony Detection in English Tweets**Cynthia Van Hee, Els Lefever, Véronique Hoste*2018 · 467 citations*](https://md.research.elamur.ai/free/en/papers/hee-2018-semeval-2018-task-3-irony/)
3. [**Multi-Modal Sarcasm Detection in Twitter with Hierarchical Fusion Model**Yitao Cai, Huiyu Cai, Xiaojun Wan*2019 · 450 citations*](https://md.research.elamur.ai/free/en/papers/cai-2019-multi-modal-sarcasm-detection-twitter/)
4. [**Harnessing Context Incongruity for Sarcasm Detection**Aditya Joshi, Vinita Sharma, Pushpak Bhattacharyya*2015 · 415 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2015-harnessing-context-incongruity-sarcasm-detection/)
5. [**Fracking Sarcasm using Neural Network**Aniruddha Ghosh, Tony Veale*2016 · 350 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2016-fracking-sarcasm-neural-network/)
6. [**A Deeper Look into Sarcastic Tweets Using Deep Convolutional Neural Networks**Soujanya Poria, Erik Cambria, Devamanyu Hazarika, et al.*2016 · 331 citations*](https://md.research.elamur.ai/free/en/papers/poria-2016-deeper-look-into-sarcastic-tweets/)
7. [**Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)**Santiago Castro, Devamanyu Hazarika, Verónica Pérez-Rosas, et al.*2019 · 313 citations*](https://md.research.elamur.ai/free/en/papers/castro-2019-towards-multimodal-sarcasm-detection-obviously/)
8. [**A Transformer-based approach to Irony and Sarcasm detection**Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis*2019 · 312 citations*](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/)
9. [**Detecting Sarcasm in Multimodal Social Platforms**Rossano Schifanella, Paloma de Juan, Joel Tetreault, et al.*2016 · 289 citations*](https://md.research.elamur.ai/free/en/papers/schifanella-2016-detecting-sarcasm-multimodal-social-platforms/)
10. [**A Large Self-Annotated Corpus for Sarcasm**Mikhail Khodak, Nikunj Saunshi, Kiran Vodrahalli*2018 · 258 citations*](https://md.research.elamur.ai/free/en/papers/khodak-2018-large-self-annotated-corpus-sarcasm/)
11. [**Reasoning with Sarcasm by Reading In-Between**Yi Tay, Anh Tuan Luu, Siu Cheung Hui, et al.*2018 · 247 citations*](https://md.research.elamur.ai/free/en/papers/tay-2018-reasoning-sarcasm-reading-between/)
12. [**Modelling Sarcasm in Twitter, a Novel Approach**Francesco Barbieri, Horacio Saggion, Francesco Ronzano*2014 · 217 citations*](https://md.research.elamur.ai/free/en/papers/barbieri-2014-modelling-sarcasm-twitter-novel-approach/)
13. [**Automatic Sarcasm Detection: A Survey**Aditya Joshi, Pushpak Bhattacharyya, Mark James Carman*2016 · 214 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2016-automatic-sarcasm-detection-survey/)
14. [**Are Word Embedding-based Features Useful for Sarcasm Detection?**Aditya Joshi, Vaibhav Tripathi, Kevin Patel, et al.*2016 · 211 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2016-are-word-embedding-based-features/)
15. [**Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association**Nan Xu, Zhixiong Zeng, Wenji Mao*2020 · 206 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-reasoning-multimodal-sarcastic-tweets-modeling/)
16. [**Tweet Sarcasm Detection Using Deep Neural Network**Meishan Zhang, Yue Zhang, Guohong Fu*2016 · 189 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2016-tweet-sarcasm-detection-deep-neural/)
17. [**Modeling Intra and Inter-modality Incongruity for Multi-Modal Sarcasm Detection**Hongliang Pan, Zheng Lin, Peng Fu, et al.*2020 · 181 citations*](https://md.research.elamur.ai/free/en/papers/pan-2020-modeling-intra-inter-modality-incongruity/)
18. [**Magnets for Sarcasm: Making Sarcasm Detection Timely, Contextual and Very Personal**Aniruddha Ghosh, Tony Veale*2017 · 174 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2017-magnets-sarcasm-making-sarcasm-detection/)
19. [**Multi-Modal Sarcasm Detection via Cross-Modal Graph Convolutional Network**Bin Liang, Chenwei Lou, Xiang Li, et al.*2022 · 172 citations*](https://md.research.elamur.ai/free/en/papers/liang-2022-multi-modal-sarcasm-detection-cross/)
20. [**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/)
21. [**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/)
22. [**Deep contextualized word representations for detecting sarcasm and irony**Suzana Ilić, Edison Marrese-Taylor, Jorge Balazs, et al.*2018 · 141 citations*](https://md.research.elamur.ai/free/en/papers/ilic-2018-deep-contextualized-word-representations-detecting/)
23. [**Sarcastic or Not: Word Embeddings to Predict the Literal or Sarcastic Meaning of Words**Debanjan Ghosh, Weiwei Guo, Smaranda Muresan*2015 · 141 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2015-sarcastic-or-not-word-embeddings/)
24. [**Learning Cognitive Features from Gaze Data for Sentiment and Sarcasm Classification using Convolutional Neural Network**Abhijit Mishra, Kuntal Dey, Pushpak Bhattacharyya*2017 · 139 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2017-learning-cognitive-features-gaze-data/)
25. [**Affective and Contextual Embedding for Sarcasm Detection**Nastaran Babanejad, Heidar Davoudi, Aijun An, et al.*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/babanejad-2020-affective-contextual-embedding-sarcasm-detection/)
26. [**From Arabic Sentiment Analysis to Sarcasm Detection: The ArSarcasm Dataset**Ibrahim Abu Farha, Walid Magdy*2020 · 132 citations*](https://md.research.elamur.ai/free/en/papers/farha-2020-arabic-sentiment-analysis-sarcasm-detection/)
27. [**Sarcasm Analysis Using Conversation Context**Debanjan Ghosh, Alexander R. Fabbri, Smaranda Muresan*2018 · 118 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2018-sarcasm-analysis-conversation-context/)
28. [**Your Sentiment Precedes You: Using an author's historical tweets to predict sarcasm**Anupam Khattri, Aditya Joshi, Pushpak Bhattacharyya, et al.*2015 · 114 citations*](https://md.research.elamur.ai/free/en/papers/khattri-2015-your-sentiment-precedes-you-author/)
29. [**Sentiment Propagation via Implicature Constraints**Lingjia Deng, Janyce Wiebe*2014 · 112 citations*](https://md.research.elamur.ai/free/en/papers/deng-2014-sentiment-propagation-implicature-constraints/)
30. [**Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation**Lotem Peled, Roi Reichart*2017 · 94 citations*](https://md.research.elamur.ai/free/en/papers/peled-2017-sarcasm-sign-interpreting-sarcasm-sentiment/)
31. [**A Report on the 2020 Sarcasm Detection Shared Task**Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan*2020 · 92 citations*](https://md.research.elamur.ai/free/en/papers/ghosh-2020-report-2020-sarcasm-detection-shared/)
32. [**CASCADE: Contextual Sarcasm Detection in Online Discussion Forums**Devamanyu Hazarika, Soujanya Poria, Sruthi Gorantla, et al.*2018 · 89 citations*](https://md.research.elamur.ai/free/en/papers/hazarika-2018-cascade-contextual-sarcasm-detection-online/)
33. [**R^3: Reverse, Retrieve, and Rank for Sarcasm Generation with Commonsense Knowledge**Tuhin Chakrabarty, Debanjan Ghosh, Smaranda Muresan, et al.*2020 · 86 citations*](https://md.research.elamur.ai/free/en/papers/chakrabarty-2020-r-textasciicircum3-reverse-retrieve-rank/)
34. [**Harnessing Cognitive Features for Sarcasm Detection**Abhijit Mishra, Diptesh Kanojia, Seema Nagar, et al.*2016 · 85 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2016-harnessing-cognitive-features-sarcasm-detection/)
35. [**Towards a Contextual Pragmatic Model to Detect Irony in Tweets**Jihen Karoui, Farah Benamara Zitoune, Véronique Moriceau, et al.*2015 · 81 citations*](https://md.research.elamur.ai/free/en/papers/karoui-2015-contextual-pragmatic-model-detect-irony/)
36. [**Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog**Shereen Oraby, Vrindavan Harrison, Amita Misra, et al.*2017 · 70 citations*](https://md.research.elamur.ai/free/en/papers/oraby-2017-are-you-serious-rhetorical-questions/)
37. [**Dynamic Routing Transformer Network for Multimodal Sarcasm Detection**Yuan Tian, Nan Xu, Ruike Zhang, et al.*2023 · 66 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-dynamic-routing-transformer-network-multimodal/)
38. [**A Novel Hierarchical BERT Architecture for Sarcasm Detection**Himani Srivastava, Vaibhav Varshney, Surabhi Kumari, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2020-novel-hierarchical-bert-architecture-sarcasm/)
39. [**Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data**Xinyu Wang, Xiaowen Sun, Tan Yang, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/)
40. [**Monday mornings are my fave :) #not Exploring the Automatic Recognition of Irony in English tweets**Cynthia Van Hee, Els Lefever, Véronique Hoste*2016 · 59 citations*](https://md.research.elamur.ai/free/en/papers/hee-2016-monday-mornings-are-my-fave/)
41. [**iSarcasm: A Dataset of Intended Sarcasm**Silviu Oprea, Walid Magdy*2020 · 57 citations*](https://md.research.elamur.ai/free/en/papers/oprea-2020-isarcasm-dataset-intended-sarcasm/)
42. [**A Modular Architecture for Unsupervised Sarcasm Generation**Abhijit Mishra, Tarun Tater, Karthik Sankaranarayanan*2019 · 51 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2019-modular-architecture-unsupervised-sarcasm-generation/)
43. [**Exploring the Realization of Irony in Twitter Data**Cynthia Van Hee, Els Lefever, Véronique Hoste*2016 · 48 citations*](https://md.research.elamur.ai/free/en/papers/hee-2016-exploring-realization-irony-twitter-data/)
44. [**Exploring Author Context for Detecting Intended vs Perceived Sarcasm**Silviu Oprea, Walid Magdy*2019 · 47 citations*](https://md.research.elamur.ai/free/en/papers/oprea-2019-exploring-author-context-detecting-intended/)
45. [**We Usually Don't Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter**Cynthia Van Hee, Els Lefever, Véronique Hoste*2018 · 39 citations*](https://md.research.elamur.ai/free/en/papers/hee-2018-we-usually-don-t-like/)
46. [**WLV at SemEval-2018 Task 3: Dissecting Tweets in Search of Irony**Omid Rohanian, Shiva Taslimipoor, Richard Evans, et al.*2018 · 39 citations*](https://md.research.elamur.ai/free/en/papers/rohanian-2018-wlv-semeval-2018-task-3/)
47. [**C-Net: Contextual Network for Sarcasm Detection**Amit Kumar Jena, Aman Sinha, Rohit Agarwal*2020 · 38 citations*](https://md.research.elamur.ai/free/en/papers/jena-2020-c-net-contextual-network-sarcasm/)
48. [**Reactive Supervision: A New Method for Collecting Sarcasm Data**Boaz Shmueli, Lun-Wei Ku, Soumya Ray*2020 · 36 citations*](https://md.research.elamur.ai/free/en/papers/shmueli-2020-reactive-supervision-new-method-collecting/)
49. [**A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict**Yiyi Liu, Yequan Wang, Aixin Sun, et al.*2022 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-dual-channel-framework-sarcasm-recognition/)
50. [**Neural Sarcasm Detection using Conversation Context**Nikhil Jaiswal*2020 · 32 citations*](https://md.research.elamur.ai/free/en/papers/jaiswal-2020-neural-sarcasm-detection-conversation-context/)
51. [**A deep-learning framework to detect sarcasm targets**Jasabanta Patro, Srijan Bansal, Animesh Mukherjee*2019 · 29 citations*](https://md.research.elamur.ai/free/en/papers/patro-2019-deep-learning-framework-detect-sarcasm/)
52. [**“When Numbers Matter!”: Detecting Sarcasm in Numerical Portions of Text**Abhijeet Dubey, Lakshya Kumar, Arpan Somani, et al.*2019 · 29 citations*](https://md.research.elamur.ai/free/en/papers/dubey-2019-when-numbers-matter-detecting-sarcasm/)
53. [**Multimodal Sarcasm Target Identification in Tweets**Jiquan Wang, Lin Sun, Yi Liu, et al.*2022 · 28 citations*](https://md.research.elamur.ai/free/en/papers/wang-2022-multimodal-sarcasm-target-identification-tweets/)
54. [**Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context**Hankyol Lee, Youngjae Yu, Gunhee Kim*2020 · 27 citations*](https://md.research.elamur.ai/free/en/papers/lee-2020-augmenting-data-sarcasm-detection-unlabeled/)
55. [**Prompt Tuning with Contradictory Intentions for Sarcasm Recognition**Yiyi Liu, Ruqing Zhang, Yixing Fan, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-tuning-contradictory-intentions-sarcasm/)
56. [**Getting Reliable Annotations for Sarcasm in Online Dialogues**Reid Swanson, Stephanie Lukin, Luke Eisenberg, et al.*2014 · 23 citations*](https://md.research.elamur.ai/free/en/papers/swanson-2014-getting-reliable-annotations-sarcasm-online/)
57. [**Generalizable Sarcasm Detection is Just Around the Corner, of Course!**Hyewon Jang, Diego Frassinelli*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/jang-2024-generalizable-sarcasm-detection-is-just/)
58. [**CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models**Zixin Chen, Hongzhan Lin, Ziyang Luo, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-cofipara-coarse-fine-paradigm-multimodal/)
59. [**Just Like a Human Would, Direct Access to Sarcasm Augmented with Potential Result and Reaction**Changrong Min, Ximing Li, Liang Yang, et al.*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/min-2023-just-like-human-would-direct/)
60. [**Sarcasm Target Identification: Dataset and An Introductory Approach**Aditya Joshi, Pranav Goel, Pushpak Bhattacharyya, et al.*2018 · 16 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2018-sarcasm-target-identification-dataset-introductory/)
61. [**Sarcasm Detection is Way Too Easy! An Empirical Comparison of Human and Machine Sarcasm Detection**Ibrahim Abu Farha, Steven Wilson, Silviu Oprea, et al.*2022 · 13 citations*](https://md.research.elamur.ai/free/en/papers/farha-2022-sarcasm-detection-is-way-too/)
62. [**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/)
63. [**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/)
64. [**Chandler: An Explainable Sarcastic Response Generator**Silviu Oprea, Steven Wilson, Walid Magdy*2021 · 8 citations*](https://md.research.elamur.ai/free/en/papers/oprea-2021-chandler-explainable-sarcastic-response-generator/)
65. [**AlexU-AL at SemEval-2022 Task 6: Detecting Sarcasm in Arabic Text Using Deep Learning Techniques**Aya Lotfy, Marwan Torki, Nagwa El-Makky*2022 · 3 citations*](https://md.research.elamur.ai/free/en/papers/lotfy-2022-alexu-al-semeval-2022-task/)
66. [**Sarc7: Evaluating Sarcasm Detection and Generation with Seven Types and Emotion-Informed Techniques**Lang Xiong, Raina Gao, Alyssa Jeong*2025*](https://md.research.elamur.ai/free/en/papers/xiong-2025-sarc7-evaluating-sarcasm-detection-generation/)
67. [**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/)

98 more papers of our library cite it; they have no page here yet.

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