---
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 ·…"
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---
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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 140884 whose bibliographies we read) · 67 with a page here, the most cited first · page 3 of 3 · [← the paper](https://md.research.elamur.ai/free/en/papers/prag-2013-riloff-sarcasm-as-contrast-between-positive/)

[← prev](https://md.research.elamur.ai/free/en/papers/prag-2013-riloff-sarcasm-as-contrast-between-positive/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/papers/prag-2013-riloff-sarcasm-as-contrast-between-positive/cited-by/) [2](https://md.research.elamur.ai/free/en/papers/prag-2013-riloff-sarcasm-as-contrast-between-positive/cited-by/page/2/) **3**

- [A deep-learning framework to detect sarcasm targets](https://md.research.elamur.ai/free/en/papers/patro-2019-deep-learning-framework-detect-sarcasm/) — Jasabanta Patro, Srijan Bansal, Animesh Mukherjee · 2019 · 29 citations
- [“When Numbers Matter!”: Detecting Sarcasm in Numerical Portions of Text](https://md.research.elamur.ai/free/en/papers/dubey-2019-when-numbers-matter-detecting-sarcasm/) — Abhijeet Dubey, Lakshya Kumar, Arpan Somani, et al. · 2019 · 29 citations
- [Multimodal Sarcasm Target Identification in Tweets](https://md.research.elamur.ai/free/en/papers/wang-2022-multimodal-sarcasm-target-identification-tweets/) — Jiquan Wang, Lin Sun, Yi Liu, et al. · 2022 · 28 citations
- [Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context](https://md.research.elamur.ai/free/en/papers/lee-2020-augmenting-data-sarcasm-detection-unlabeled/) — Hankyol Lee, Youngjae Yu, Gunhee Kim · 2020 · 27 citations
- [Prompt Tuning with Contradictory Intentions for Sarcasm Recognition](https://md.research.elamur.ai/free/en/papers/liu-2023-prompt-tuning-contradictory-intentions-sarcasm/) — Yiyi Liu, Ruqing Zhang, Yixing Fan, et al. · 2023 · 24 citations
- [Getting Reliable Annotations for Sarcasm in Online Dialogues](https://md.research.elamur.ai/free/en/papers/swanson-2014-getting-reliable-annotations-sarcasm-online/) — Reid Swanson, Stephanie Lukin, Luke Eisenberg, et al. · 2014 · 23 citations
- [Generalizable Sarcasm Detection is Just Around the Corner, of Course!](https://md.research.elamur.ai/free/en/papers/jang-2024-generalizable-sarcasm-detection-is-just/) — Hyewon Jang, Diego Frassinelli · 2024 · 22 citations
- [CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/chen-2024-cofipara-coarse-fine-paradigm-multimodal/) — Zixin Chen, Hongzhan Lin, Ziyang Luo, et al. · 2024 · 20 citations
- [Just Like a Human Would, Direct Access to Sarcasm Augmented with Potential Result and Reaction](https://md.research.elamur.ai/free/en/papers/min-2023-just-like-human-would-direct/) — Changrong Min, Ximing Li, Liang Yang, et al. · 2023 · 16 citations
- [Sarcasm Target Identification: Dataset and An Introductory Approach](https://md.research.elamur.ai/free/en/papers/joshi-2018-sarcasm-target-identification-dataset-introductory/) — Aditya Joshi, Pranav Goel, Pushpak Bhattacharyya, et al. · 2018 · 16 citations
- [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/) — Ibrahim Abu Farha, Steven Wilson, Silviu Oprea, et al. · 2022 · 13 citations
- [Interpreting Verbal Irony: Linguistic Strategies and the Connection to the Type of Semantic Incongruity](https://md.research.elamur.ai/free/en/papers/ghosh-2020-interpreting-verbal-irony-linguistic-strategies/) — Debanjan Ghosh, Elena Musi, Smaranda Muresan · 2020 · 10 citations
- [How Challenging is Sarcasm versus Irony Classification?: A Study With a Dataset from English Literature](https://md.research.elamur.ai/free/en/papers/joshi-2016-how-challenging-is-sarcasm-versus/) — Aditya Joshi, Vaibhav Tripathi, Pushpak Bhattacharyya, et al. · 2016 · 10 citations
- [Chandler: An Explainable Sarcastic Response Generator](https://md.research.elamur.ai/free/en/papers/oprea-2021-chandler-explainable-sarcastic-response-generator/) — Silviu Oprea, Steven Wilson, Walid Magdy · 2021 · 8 citations
- [AlexU-AL at SemEval-2022 Task 6: Detecting Sarcasm in Arabic Text Using Deep Learning Techniques](https://md.research.elamur.ai/free/en/papers/lotfy-2022-alexu-al-semeval-2022-task/) — Aya Lotfy, Marwan Torki, Nagwa El-Makky · 2022 · 3 citations
- [Sarc7: Evaluating Sarcasm Detection and Generation with Seven Types and Emotion-Informed Techniques](https://md.research.elamur.ai/free/en/papers/xiong-2025-sarc7-evaluating-sarcasm-detection-generation/) — Lang Xiong, Raina Gao, Alyssa Jeong · 2025
- [Linguistic Features in Automatic Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/ducret-2020-linguistic-features-automatic-sarcasm-detection/) — Martina Ducret, Lauren Kruse, Carlos Martinez, et al. · 2020

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