# Sarcasm SIGN: Interpreting Sarcasm with Sentiment Based Monolingual Machine Translation

arXiv: https://arxiv.org/abs/1704.06836 · HTML: https://mlsanity.com/paper/1704.06836/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2017.

## Built on by (most cited first, 18 of 18)

- [When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialogues](https://mlsanity.com/paper/2203.06419/) (2022)
- [Figurative Language in Recognizing Textual Entailment](https://mlsanity.com/paper/2106.01195/) (2021)
- [Nice perfume. How long did you marinate in it? Multimodal Sarcasm Explanation](https://mlsanity.com/paper/2112.04873/) (2021)
- [Multi-source Semantic Graph-based Multimodal Sarcasm Explanation Generation](https://mlsanity.com/paper/2306.16650/) (2023)
- [Sentiment Analysis through LLM Negotiations](https://mlsanity.com/paper/2311.01876/) (2023)
- [!Qu'e maravilla! Multimodal Sarcasm Detection in Spanish: a Dataset and a Baseline](https://mlsanity.com/paper/2105.05542/) (2021)
- [Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal Dialogues](https://mlsanity.com/paper/2211.11049/) (2022)
- [Sentiment-enhanced Graph-based Sarcasm Explanation in Dialogue](https://mlsanity.com/paper/2402.03658/) (2024)
- [From Theories on Styles to their Transfer in Text: Bridging the Gap with a Hierarchical Survey](https://mlsanity.com/paper/2110.15871/) (2021)
- [Target-Augmented Shared Fusion-based Multimodal Sarcasm Explanation Generation](https://mlsanity.com/paper/2502.07391/) (2025)
- [Multi-Figurative Language Generation](https://mlsanity.com/paper/2209.01835/) (2022)
- [KoCoSa: Korean Context-aware Sarcasm Detection Dataset](https://mlsanity.com/paper/2402.14428/) (2024)
- [Revealing the impact of synthetic native samples and multi-tasking strategies in Hindi-English code-mixed humour and sarcasm detection](https://mlsanity.com/paper/2412.12761/) (2024)
- [Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature](https://mlsanity.com/paper/2106.05752/) (2021)
- [How to Describe Images in a More Funny Way? Towards a Modular Approach to Cross-Modal Sarcasm Generation](https://mlsanity.com/paper/2211.10992/) (2022)
- [SinFoS: A Parallel Dataset for Translating Sinhala Figures of Speech](https://mlsanity.com/paper/2602.09866/) (2026)
- [Researchers eye-view of sarcasm detection in social media textual content](https://mlsanity.com/paper/2304.08582/) (2023)
- [When Do "More Contexts" Help with Sarcasm Recognition?](https://mlsanity.com/paper/2403.12469/) (2024)

## Abstract (arXiv)

Sarcasm is a form of speech in which speakers say the opposite of what they truly mean in order to convey a strong sentiment. In other words, "Sarcasm is the giant chasm between what I say, and the person who doesn't get it.". In this paper we present the novel task of sarcasm interpretation, defined as the generation of a non-sarcastic utterance conveying the same message as the original sarcastic one. We introduce a novel dataset of 3000 sarcastic tweets, each interpreted by five human judges. Addressing the task as monolingual machine translation (MT), we experiment with MT algorithms and evaluation measures. We then present SIGN: an MT based sarcasm interpretation algorithm that targets sentiment words, a defining element of textual sarcasm. We show that while the scores of n-gram based automatic measures are similar for all interpretation models, SIGN's interpretations are scored higher by humans for adequacy and sentiment polarity. We conclude with a discussion on future research directions for our new task.