Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
csv
Languages:
Bengali
Size:
10K - 100K
License:
Update README.md
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README.md
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license: mit
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---
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license: mit
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task_categories:
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- text-classification
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language:
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- bn
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pretty_name: BnSentMix
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size_categories:
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- 10K<n<100K
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---
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# BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis
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[](https://github.com/Nishita2000/BnSentMix)
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## Dataset Overview
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Column Title | Description
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------------ | -------------
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`Data Sources` | Facebook, YouTube, E-commerce Sites
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`#Samples` | 20000
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`Sentiment Labels` | 1:Positive, 2:Negative, 3:Neutral, 4:Mixed
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`Filtering Method` | Automated using `mBERT`
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`#Annotators` | 64
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`Annotation/Sample` | 2 or 3 (if tie)
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## Dataset Statistics
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| Statistic | Value |
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|-------------------------|--------|
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| Mean Character Length | 62.77 |
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| Max Character Length | 1985 |
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| Min Character Length | 14 |
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| Mean Word Count | 11.65 |
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| Max Word Count | 368 |
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| Min Word Count | 4 |
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| Unique Word Count | 37734 |
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| Unique Sentence Count | 21873 |
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## Citation
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If you find this work useful, please cite our paper:
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```bib
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@misc{alam2024bnsentmixdiversebengalienglishcodemixed,
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title={BnSentMix: A Diverse Bengali-English Code-Mixed Dataset for Sentiment Analysis},
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author={Sadia Alam and Md Farhan Ishmam and Navid Hasin Alvee and Md Shahnewaz Siddique and Md Azam Hossain and Abu Raihan Mostofa Kamal},
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year={2024},
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eprint={2408.08964},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2408.08964},
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}
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```
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