---
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