# A Corpus of English-Hindi Code-Mixed Tweets for Sarcasm Detection

arXiv: https://arxiv.org/abs/1805.11869 · HTML: https://mlsanity.com/paper/1805.11869/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2018.

## Built on by (most cited first, 15 of 15)

- [Multi-modal Sarcasm Detection and Humor Classification in Code-mixed Conversations](https://mlsanity.com/paper/2105.09984/) (2021)
- [When did you become so smart, oh wise one?! Sarcasm Explanation in Multi-modal Multi-party Dialogues](https://mlsanity.com/paper/2203.06419/) (2022)
- [HinGE: A Dataset for Generation and Evaluation of Code-Mixed Hinglish Text](https://mlsanity.com/paper/2107.03760/) (2021)
- [Challenges and Limitations with the Metrics Measuring the Complexity of Code-Mixed Text](https://mlsanity.com/paper/2106.10123/) (2021)
- [COMI-LINGUA: Expert Annotated Large-Scale Dataset for Multitask NLP in Hindi-English Code-Mixing](https://mlsanity.com/paper/2503.21670/) (2025)
- [Explaining (Sarcastic) Utterances to Enhance Affect Understanding in Multimodal Dialogues](https://mlsanity.com/paper/2211.11049/) (2022)
- [Systematic Literature Review: Computational Approaches for Humour Style Classification](https://mlsanity.com/paper/2402.01759/) (2024)
- [The Effectiveness of Intermediate-Task Training for Code-Switched Natural Language Understanding](https://mlsanity.com/paper/2107.09931/) (2021)
- [Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data](https://mlsanity.com/paper/2305.15722/) (2023)
- [Nipping in the Bud: Detection, Diffusion and Mitigation of Hate Speech on Social Media](https://mlsanity.com/paper/2201.00961/) (2022)
- [Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challenges](https://mlsanity.com/paper/2401.09244/) (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)
- [How Effective is Incongruity? Implications for Code-mix Sarcasm Detection](https://mlsanity.com/paper/2202.02702/) (2022)
- [MixSarc: A Bangla-English Code-Mixed Corpus for Implicit Meaning Identification](https://mlsanity.com/paper/2602.21608/) (2026)
- [Yor-Sarc: A gold-standard dataset for sarcasm detection in a low-resource African language](https://mlsanity.com/paper/2602.18964/) (2026)

## Abstract (arXiv)

Social media platforms like twitter and facebook have be- come two of the largest mediums used by people to express their views to- wards different topics. Generation of such large user data has made NLP tasks like sentiment analysis and opinion mining much more important. Using sarcasm in texts on social media has become a popular trend lately. Using sarcasm reverses the meaning and polarity of what is implied by the text which poses challenge for many NLP tasks. The task of sarcasm detection in text is gaining more and more importance for both commer- cial and security services. We present the first English-Hindi code-mixed dataset of tweets marked for presence of sarcasm and irony where each token is also annotated with a language tag. We present a baseline su- pervised classification system developed using the same dataset which achieves an average F-score of 78.4 after using random forest classifier and performing 10-fold cross validation.