# Dataset Citations for BanglaSenti Dataset Preparation

## Bangla Sentiment Dataset (Kaggle)
- Source: [tasrifnurhimel/sentiment-dataset-bangla-text](https://www.kaggle.com/datasets/tasrifnurhimel/sentiment-dataset-bangla-text)
- License: Apache 2.0

## Bangla Sentiments in eLearning (Hugging Face)
- Source: [TanjimKIT/Bangla_Sentiments_in_eLearning](https://huggingface.co/datasets/TanjimKIT/Bangla_Sentiments_in_eLearning)
- License: Apache 2.0
- DOI: 10.57967/hf/3334

@article{rahman2024analyzing,
  title={Analyzing sentiments in elearning: A comparative study of bangla and romanized bangla text using transformers},
  author={Rahman, Md Akash and Begum, Manoara and Mahmud, Tanjim and Hossain, Mohammad Shahadat and Andersson, Karl},
  journal={IEEE Access},
  year={2024},
  publisher={IEEE}
}

## Bengali Sentiment Classification (Kaggle)
- Source: [saurabhshahane/bengali-sentiment-classification](https://www.kaggle.com/datasets/saurabhshahane/bengali-sentiment-classification)
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- Attribution: Sazzed, Salim (2021), “Bangla (Bengali) sentiment analysis classification benchmark dataset corpus”, Mendeley Data, V4, doi: 10.17632/p6zc7krs37.4

@dataset{sazzed2021bangla,
  author = {Sazzed, Salim},
  title = {Bangla (Bengali) sentiment analysis classification benchmark dataset corpus},
  year = {2021},
  publisher = {Mendeley Data},
  version = {V4},
  doi = {10.17632/p6zc7krs37.4},
  url = {https://data.mendeley.com/datasets/p6zc7krs37/4}
}

## BanglaBook Review Dataset (GitHub)
- Source: [mohsinulkabir14/BanglaBook](https://github.com/mohsinulkabir14/BanglaBook/tree/main/data/csv)
- License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

@inproceedings{kabir-etal-2023-banglabook,
    title = "{B}angla{B}ook: A Large-scale {B}angla Dataset for Sentiment Analysis from Book Reviews",
    author = "Kabir, Mohsinul  and Bin Mahfuz, Obayed  and Raiyan, Syed Rifat  and Mahmud, Hasan  and Hasan, Md Kamrul",
    booktitle = "Findings of the Association for Computational Linguistics: ACL 2023",
    month = jul,
    year = "2023",
    address = "Toronto, Canada",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.findings-acl.80",
    pages = "1237--1247"
}

## Bangla Sentiment Dataset (Mendeley)
- Source: [Mendeley Data - Biswas, Jahanur; Hasan, Nahid (2025)](https://data.mendeley.com/datasets/rh67mckhbh/2)
- License: Creative Commons Attribution 4.0 International (CC BY 4.0)
- DOI: 10.17632/rh67mckhbh.2

@dataset{biswas2025bangla,
  author = {Biswas, Jahanur and Hasan, Nahid},
  title = {Bangla Sentiment Dataset},
  year = {2025},
  publisher = {Mendeley Data},
  version = {V2},
  doi = {10.17632/rh67mckhbh.2},
  url = {https://data.mendeley.com/datasets/rh67mckhbh/2}
}

## Synthetic Bengali Sentiment (Hugging Face)
- Source: [shaikh25/synthetic-bengali-sentiment](https://huggingface.co/datasets/shaikh25/synthetic-bengali-sentiment)
- License: Apache 2.0

@dataset{rahman_bengali_sentiment_2025,
  title={Bengali Sentiment Analysis Dataset},
  author={Rahman, MD Shaikh},
  year={2025},
  url={https://huggingface.co/datasets/shaikh25/bengali-sentiment-dataset},
  note={Synthetic Bengali sentiment dataset generated using ChatGPT}
}

## Bengali Sentiment Noisy Dataset (Hugging Face)
- Source: [sustcsenlp/bn_sentiment_noisy_dataset](https://huggingface.co/datasets/sustcsenlp/bn_sentiment_noisy_dataset)
- License: Apache 2.0

@inproceedings{islam2021sentnob,
  title={SentNoB: A Dataset for Analysing Sentiment on Noisy Bangla Texts},
  author={Islam, Khondoker Ittehadul and Kar, Sudipta and Islam, Md Saiful and Amin, Mohammad Ruhul},
  booktitle={Findings of the Association for Computational Linguistics: EMNLP 2021},
  pages={3265--3271},
  year={2021}
}


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All datasets are used and attributed according to their respective licenses for open-source and academic delivery.

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**Repository Usage:**
- This repository is intended for public, academic, and downstream use. Please cite this repo and the original datasets in any derived work or publication.
- For integration, link this repo as the data source in your main project documentation.