# Code-switching patterns can be an effective route to improve performance of downstream NLP applications: A case study of humour, sarcasm and hate speech detection

arXiv: https://arxiv.org/abs/2005.02295 · HTML: https://mlsanity.com/paper/2005.02295/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 May 2020.

## Built on by (most cited first, 12 of 12)

- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives](https://mlsanity.com/paper/2209.04712/) (2022)
- [HIT: A Hierarchically Fused Deep Attention Network for Robust Code-mixed Language Representation](https://mlsanity.com/paper/2105.14600/) (2021)
- [Persona-aware Generative Model for Code-mixed Language](https://mlsanity.com/paper/2309.02915/) (2023)
- [A Comprehensive Understanding of Code-mixed Language Semantics using Hierarchical Transformer](https://mlsanity.com/paper/2204.12753/) (2022)
- [Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challenges](https://mlsanity.com/paper/2401.09244/) (2024)
- [How Effective is Incongruity? Implications for Code-mix Sarcasm Detection](https://mlsanity.com/paper/2202.02702/) (2022)
- [Automatic Identification of Motivation for Code-Switching in Speech Transcripts](https://mlsanity.com/paper/2212.08565/) (2022)
- [IISERB Brains at SemEval 2022 Task 6: A Deep-learning Framework to Identify Intended Sarcasm in English](https://mlsanity.com/paper/2203.02244/) (2022)
- [Cordyceps@LT-EDI: Patching Language-Specific Homophobia/Transphobia Classifiers with a Multilingual Understanding](https://mlsanity.com/paper/2309.13561/) (2023)
- [Large Language Models for Toxic Language Detection in Low-Resource Balkan Languages](https://mlsanity.com/paper/2506.09992/) (2025)
- [Global Beats, Local Tongue: Studying Code Switching in K-pop Hits on Billboard Charts](https://mlsanity.com/paper/2509.23197/) (2025)

## Abstract (arXiv)

In this paper we demonstrate how code-switching patterns can be utilised to improve various downstream NLP applications. In particular, we encode different switching features to improve humour, sarcasm and hate speech detection tasks. We believe that this simple linguistic observation can also be potentially helpful in improving other similar NLP applications.