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---
license: mit
task_categories:
- text-classification
language:
- bn
- en
- hi
pretty_name: Bengali-English Code-Mixed Sentiment Dataset
size_categories:
- 10K<n<100K
---
# Bengali-English Code-Mixed Sentiment Dataset
## Dataset Summary
This dataset contains **Bengali–English code-mixed social media text** annotated for sentiment classification.
The primary goal is to support research and applications in **code-mixed NLP**, especially sentiment analysis in low-resource Indic languages.
The dataset combines and cleans multiple publicly available sources:
- **BnSentMix**: Bengali–English code-mixed sentiment dataset
- **SentMix-3L**: Multi-lingual code-mixed dataset (Bengali–English–Hindi subset used)
- **Kaggle code-mixed sentiment dataset**
We unified the label scheme into three sentiment classes:
- `positive`
- `negative`
- `neutral`
## Supported Tasks
- **Text Classification / Sentiment Analysis**
- **Code-Mixed NLP Research**
- **Low-Resource Language Modeling**
## Languages
- Bengali (code-mixed with Roman script)
- English
## Dataset Structure
### Data Fields
- **text**: (string) Input sentence in Bengali-English code-mixed text
- **label**: (string) Sentiment label → `positive`, `negative`, `neutral`, `mixed`
### Splits
- **train**: 16,012 examples
- **validation**: 2,002 examples
- **test**: 2,002 examples
## Example
```json
{
"text": "Aaj movie ta khub bhalo chilo! Totally loved it.",
"label": "positive"
}
```
## Usage
```python
from datasets import load_dataset
ds = load_dataset("Swarnadeep-28/bn_code_mix_sentiment_dataset")
print(ds["train"][0])
```
## Dataset Creation
- **Source datasets**: BnSentMix, SentMix-3L, Kaggle
- **Preprocessing**: label unification, text cleaning, removal of duplicates
- **License**: MIT (respect original dataset licenses if reused)
## Citation
If you use this dataset in your research, please cite:
> @dataset{das2025_bn_code_mix_sentiment,
author = {Swarnadeep Das},
title = {Bengali-English Code-Mixed Sentiment Dataset},
year = {2025},
url = {https://huggingface.co/datasets/Swarnadeep-28/bn_code_mix_sentiment_dataset}
}
## Limitations
Informal Romanized Bengali text may vary widely (spellings/slang).
Small proportion of neutral/mixed cases compared to positive/negative.
Not designed for toxic/abusive language detection.
## Acknowledgements
This dataset builds on the work of:
- BnSentMix
- SentMix-3L
- Kaggle Code-Mixed Dataset Contributors |