# A Sentiment Analysis Dataset for Code-Mixed Malayalam-English

arXiv: https://arxiv.org/abs/2006.00210 · HTML: https://mlsanity.com/paper/2006.00210/

## Key facts

- Cited by 50 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 May 2020.

## Built on by (most cited first, 30 of 50)

- [Multilingual Large Language Models Are Not (Yet) Code-Switchers](https://mlsanity.com/paper/2305.14235/) (2023)
- [The Decades Progress on Code-Switching Research in NLP: A Systematic Survey on Trends and Challenges](https://mlsanity.com/paper/2212.09660/) (2022)
- [DravidianCodeMix: Sentiment Analysis and Offensive Language Identification Dataset for Dravidian Languages in Code-Mixed Text](https://mlsanity.com/paper/2106.09460/) (2021)
- [Memotion 3: Dataset on Sentiment and Emotion Analysis of Codemixed Hindi-English Memes](https://mlsanity.com/paper/2303.09892/) (2023)
- [SJ_AJ@DravidianLangTech-EACL2021: Task-Adaptive Pre-Training of Multilingual BERT models for Offensive Language Identification](https://mlsanity.com/paper/2102.01051/) (2021)
- [Comparing Approaches to Dravidian Language Identification](https://mlsanity.com/paper/2103.05552/) (2021)
- [Social Intelligence Data Infrastructure: Structuring the Present and Navigating the Future](https://mlsanity.com/paper/2403.14659/) (2024)
- [MINERS: Multilingual Language Models as Semantic Retrievers](https://mlsanity.com/paper/2406.07424/) (2024)
- [BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis](https://mlsanity.com/paper/2408.08964/) (2024)
- [CodeMixBench: Evaluating Code-Mixing Capabilities of LLMs Across 18 Languages](https://mlsanity.com/paper/2507.18791/) (2025)
- [NLP-CUET@DravidianLangTech-EACL2021: Offensive Language Detection from Multilingual Code-Mixed Text using Transformers](https://mlsanity.com/paper/2103.00455/) (2021)
- [Hate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection](https://mlsanity.com/paper/2102.10084/) (2021)
- [Unsupervised Self-Training for Sentiment Analysis of Code-Switched Data](https://mlsanity.com/paper/2103.14797/) (2021)
- [Hope Speech detection in under-resourced Kannada language](https://mlsanity.com/paper/2108.04616/) (2021)
- [Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexicon](https://mlsanity.com/paper/2402.02113/) (2024)
- [Sentiment Analysis of Persian-English Code-mixed Texts](https://mlsanity.com/paper/2102.12700/) (2021)
- [IIITT@LT-EDI-EACL2021-Hope Speech Detection: There is always Hope in Transformers](https://mlsanity.com/paper/2104.09066/) (2021)
- [Offensive Language Identification in Low-resourced Code-mixed Dravidian languages using Pseudo-labeling](https://mlsanity.com/paper/2108.12177/) (2021)
- [Offense Detection in Dravidian Languages using Code-Mixing Index based Focal Loss](https://mlsanity.com/paper/2111.06916/) (2021)
- [Multilingual Prompt Engineering in Large Language Models: A Survey Across NLP Tasks](https://mlsanity.com/paper/2505.11665/) (2025)
- [Task-Specific Pre-Training and Cross Lingual Transfer for Code-Switched Data](https://mlsanity.com/paper/2102.12407/) (2021)
- [UVCE-IIITT@DravidianLangTech-EACL2021: Tamil Troll Meme Classification: You need to Pay more Attention](https://mlsanity.com/paper/2104.09081/) (2021)
- [A Multilingual Dataset of COVID-19 Vaccination Attitudes on Twitter](https://mlsanity.com/paper/2206.14619/) (2022)
- [indicnlp@kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages](https://mlsanity.com/paper/2102.07150/) (2021)
- [Cross-Lingual Text Classification of Transliterated Hindi and Malayalam](https://mlsanity.com/paper/2108.13620/) (2021)
- [Leveraging Large Language Models for Code-Mixed Data Augmentation in Sentiment Analysis](https://mlsanity.com/paper/2411.00691/) (2024)
- [What talking you?: Translating Code-Mixed Messaging Texts to English](https://mlsanity.com/paper/2411.05253/) (2024)
- [CMSAOne@Dravidian-CodeMix-FIRE2020: A Meta Embedding and Transformer model for Code-Mixed Sentiment Analysis on Social Media Text](https://mlsanity.com/paper/2101.09004/) (2021)
- [KBCNMUJAL@HASOC-Dravidian-CodeMix-FIRE2020: Using Machine Learning for Detection of Hate Speech and Offensive Code-Mixed Social Media text](https://mlsanity.com/paper/2102.09866/) (2021)
- [Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns](https://mlsanity.com/paper/2211.07628/) (2022)

## Abstract (arXiv)

There is an increasing demand for sentiment analysis of text from social media which are mostly code-mixed. Systems trained on monolingual data fail for code-mixed data due to the complexity of mixing at different levels of the text. However, very few resources are available for code-mixed data to create models specific for this data. Although much research in multilingual and cross-lingual sentiment analysis has used semi-supervised or unsupervised methods, supervised methods still performs better. Only a few datasets for popular languages such as English-Spanish, English-Hindi, and English-Chinese are available. There are no resources available for Malayalam-English code-mixed data. This paper presents a new gold standard corpus for sentiment analysis of code-mixed text in Malayalam-English annotated by voluntary annotators. This gold standard corpus obtained a Krippendorff's alpha above 0.8 for the dataset. We use this new corpus to provide the benchmark for sentiment analysis in Malayalam-English code-mixed texts.