# Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017

arXiv: https://arxiv.org/abs/1803.06745 · HTML: https://mlsanity.com/paper/1803.06745/

## Key facts

- Cited by 24 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Mar 2018.

## Built on by (most cited first, 24 of 24)

- [L3CubeMahaSent: A Marathi Tweet-based Sentiment Analysis Dataset](https://mlsanity.com/paper/2103.11408/) (2021)
- [Experimental Evaluation of Deep Learning models for Marathi Text Classification](https://mlsanity.com/paper/2101.04899/) (2021)
- [Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settings](https://mlsanity.com/paper/2410.13153/) (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)
- [CodemixedNLP: An Extensible and Open NLP Toolkit for Code-Mixing](https://mlsanity.com/paper/2106.06004/) (2021)
- [Exploring Methods for Building Dialects-Mandarin Code-Mixing Corpora: A Case Study in Taiwanese Hokkien](https://mlsanity.com/paper/2301.08937/) (2023)
- [Sentiment Analysis of Persian-English Code-mixed Texts](https://mlsanity.com/paper/2102.12700/) (2021)
- [Task-Specific Pre-Training and Cross Lingual Transfer for Code-Switched Data](https://mlsanity.com/paper/2102.12407/) (2021)
- [GupShup: An Annotated Corpus for Abstractive Summarization of Open-Domain Code-Switched Conversations](https://mlsanity.com/paper/2104.08578/) (2021)
- [On the logistical difficulties and findings of Jopara Sentiment Analysis](https://mlsanity.com/paper/2105.02947/) (2021)
- [What talking you?: Translating Code-Mixed Messaging Texts to English](https://mlsanity.com/paper/2411.05253/) (2024)
- [AdvCodeMix: Adversarial Attack on Code-Mixed Data](https://mlsanity.com/paper/2111.00350/) (2021)
- [Comparative Study of Pre-Trained BERT Models for Code-Mixed Hindi-English Data](https://mlsanity.com/paper/2305.15722/) (2023)
- [The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages](https://mlsanity.com/paper/2310.14557/) (2023)
- [Multilingual Controlled Generation And Gold-Standard-Agnostic Evaluation of Code-Mixed Sentences](https://mlsanity.com/paper/2410.10580/) (2024)
- [CoLI-Machine Learning Approaches for Code-mixed Language Identification at the Word Level in Kannada-English Texts](https://mlsanity.com/paper/2211.09847/) (2022)
- [CONFLATOR: Incorporating Switching Point based Rotatory Positional Encodings for Code-Mixed Language Modeling](https://mlsanity.com/paper/2309.05270/) (2023)
- [Progressive Sentiment Analysis for Code-Switched Text Data](https://mlsanity.com/paper/2210.14380/) (2022)
- [BhashaSutra: A Task-Centric Unified Survey of Indian NLP Datasets, Corpora, and Resources](https://mlsanity.com/paper/2604.18423/) (2026)
- [Sentiment Analysis of Code-Mixed Social Media Text (Hinglish)](https://mlsanity.com/paper/2102.12149/) (2021)
- [JU_NLP at HinglishEval: Quality Evaluation of the Low-Resource Code-Mixed Hinglish Text](https://mlsanity.com/paper/2206.08053/) (2022)
- [Leveraging Language Identification to Enhance Code-Mixed Text Classification](https://mlsanity.com/paper/2306.04964/) (2023)
- [IndicTriMix: Developing Language Identification Datasets and Models for Tri-Language Code-Mixing](https://mlsanity.com/paper/2609.11851/) (2026)

## Abstract (arXiv)

Sentiment analysis is essential in many real-world applications such as stance detection, review analysis, recommendation system, and so on. Sentiment analysis becomes more difficult when the data is noisy and collected from social media. India is a multilingual country; people use more than one languages to communicate within themselves. The switching in between the languages is called code-switching or code-mixing, depending upon the type of mixing. This paper presents overview of the shared task on sentiment analysis of code-mixed data pairs of Hindi-English and Bengali-English collected from the different social media platform. The paper describes the task, dataset, evaluation, baseline and participant's systems.