# Sentiment Analysis of Persian-English Code-mixed Texts

arXiv: https://arxiv.org/abs/2102.12700 · HTML: https://mlsanity.com/paper/2102.12700/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 27 references that are in the map.
- First posted on arXiv 25 Feb 2021.

## Builds on (most cited first, 14 of 14)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation](https://mlsanity.com/paper/2005.04322/) (2020)
- [Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Text](https://mlsanity.com/paper/2006.00206/) (2020)
- [SemEval-2020 Task 9: Overview of Sentiment Analysis of Code-Mixed Tweets](https://mlsanity.com/paper/2008.04277/) (2020)
- [A Sentiment Analysis Dataset for Code-Mixed Malayalam-English](https://mlsanity.com/paper/2006.00210/) (2020)
- [SciPy 1.0--Fundamental Algorithms for Scientific Computing in Python](https://mlsanity.com/paper/1907.10121/) (2019)
- [Towards Sub-Word Level Compositions for Sentiment Analysis of Hindi-English Code Mixed Text](https://mlsanity.com/paper/1611.00472/) (2016)
- [Sentiment Analysis of Code-Mixed Indian Languages: An Overview of SAIL_Code-Mixed Shared Task @ICON-2017](https://mlsanity.com/paper/1803.06745/) (2018)
- [Preparing Bengali-English Code-Mixed Corpus for Sentiment Analysis of Indian Languages](https://mlsanity.com/paper/1803.04000/) (2018)
- [Automatic Normalization of Word Variations in Code-Mixed Social Media Text](https://mlsanity.com/paper/1804.00804/) (2018)
- [An Ensemble Model for Sentiment Analysis of Hindi-English Code-Mixed Data](https://mlsanity.com/paper/1806.04450/) (2018)
- [IIT Gandhinagar at SemEval-2020 Task 9: Code-Mixed Sentiment Classification Using Candidate Sentence Generation and Selection](https://mlsanity.com/paper/2006.14465/) (2020)
- [Sentiment Identification in Code-Mixed Social Media Text](https://mlsanity.com/paper/1707.01184/) (2017)
- [LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis](https://mlsanity.com/paper/2008.13173/) (2020)

## Built on by (most cited first, 6 of 6)

- [BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis](https://mlsanity.com/paper/2408.08964/) (2024)
- [Sentiment Analysis of Persian Language: Review of Algorithms, Approaches and Datasets](https://mlsanity.com/paper/2212.06041/) (2022)
- [PRFashion24: A Dataset for Sentiment Analysis of Fashion Products Reviews in Persian](https://mlsanity.com/paper/2405.18060/) (2024)
- [On Importance of Code-Mixed Embeddings for Hate Speech Identification](https://mlsanity.com/paper/2411.18577/) (2024)
- [Exploring Subjective Tasks in Farsi: A Survey Analysis and Evaluation of Language Models](https://mlsanity.com/paper/2509.05719/) (2025)
- [PERCEPT: A Corpus for POS Tagging and Analysis of Persian-English Code-Mixing](https://mlsanity.com/paper/2608.10109/) (2026)

## Abstract (arXiv)

The rapid production of data on the internet and the need to understand how users are feeling from a business and research perspective has prompted the creation of numerous automatic monolingual sentiment detection systems. More recently however, due to the unstructured nature of data on social media, we are observing more instances of multilingual and code-mixed texts. This development in content type has created a new demand for code-mixed sentiment analysis systems. In this study we collect, label and thus create a dataset of Persian-English code-mixed tweets. We then proceed to introduce a model which uses BERT pretrained embeddings as well as translation models to automatically learn the polarity scores of these Tweets. Our model outperforms the baseline models that use Na"ive Bayes and Random Forest methods.