README.md

---
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
- zero-shot-classification
language:
- bn
tags:
- Sentiment Analysis
- Book Reviews
- Product Reviews
- Bangla
- Bengali
- Dataset
pretty_name: BanglaBook
size_categories:
- 100K<n<1M
---
# BᴀɴɢʟᴀBᴏᴏᴋ: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews
This repository contains the code, data, and models of the paper titled "BᴀɴɢʟᴀBᴏᴏᴋ: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews" published in the ***Findings of the Association for Computational Linguistics: ACL 2023***.

[![arXiv](https://img.shields.io/badge/arXiv-2305.06595-b31b1b.svg?logo=arxiv)](https://arxiv.org/abs/2305.06595)
[![anthology](https://img.shields.io/badge/ACL%20Anthology-2023.findings--acl.80-EE161F.svg)](https://aclanthology.org/2023.findings-acl.80/)
[![GoogleScholar](https://img.shields.io/badge/Google%20Scholar-4285F4?style=flat&logo=Google+Scholar&logoColor=white&color=gray&labelColor=4285F4)](https://tinyurl.com/gscholarbanglabook)
[![ResearchGate](https://img.shields.io/badge/ResearchGate-00CCBB?style=flat&logo=ResearchGate&logoColor=white&color=gray&labelColor=00CCBB)](https://www.researchgate.net/publication/370688086_BanglaBook_A_Large-scale_Bangla_Dataset_for_Sentiment_Analysis_from_Book_Reviews)

[![PDF](https://img.shields.io/badge/Paper%20PDF-EF3939?style=flat&logo=adobeacrobatreader&logoColor=white&color=gray&labelColor=ec1c24)](https://aclanthology.org/2023.findings-acl.80.pdf)
[![Slides](https://img.shields.io/badge/Slides%20PDF-EF3939?style=flat&logo=Microsoft+PowerPoint&logoColor=white&color=gray&labelColor=B7472A)](https://drive.google.com/file/d/1-UkYs_Rx11S7qKOfR-6rnO2VDp3W78vQ/view?usp=sharing)
[![Video](https://img.shields.io/badge/Video%20Presentation-4285F4?style=flat&logo=data:image/svg%2bxml;base64,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&logoColor=white&color=gray&labelColor=B197FC)](https://aclanthology.org/2023.findings-acl.80.mp4)

**License:** Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

[![license](https://arxiv.org/icons/licenses/by-nc-sa-4.0.png)](http://creativecommons.org/licenses/by-nc-sa/4.0/)

## Data Format
Each row consists of a book review sample. The table below describes what each column signifies.

Column Title | Description
------------ | -------------
`id` | The unique identification number of the sample
`Book_Name` | The title of the book that has been evaluated by the review
`Writer_Name` | The name of the book's author
`Category` | The genre to which the book belongs
`Rating` | A numerical value \\(r\\) such that \\(1\leq r \leq 5\\)<br>A score reflecting the reviewer's subjective assessment of the book's quality
`Review` | The review text written by the reviewer
`Site` | The name of the online bookshop
`sentiment` | The conveyed sentiment and class label of the review<br>For a review sample \\(i\\) with rating \\(r_i\\), the sentiment label \\(S_i\\) is,<br>
$$
S_i =\begin{cases} 
\text{Negative}, & \text{if } r_i \leq 2\\
\text{Neutral}, & \text{if } r_i = 3\\
\text{Positive}, & \text{if }r_i \geq 4
\end{cases}
$$
`label` | The numerical representation of the sentiment label<br>For a review sample \\(i\\) with sentiment label \\(S_i\\), the numerical label is,<br>
$$label_i = \begin{cases} 0, &\text{if } S_i = \text{Negative} \\ 1, &\text{if } S_i = \text{Neutral} \\ 2, &\text{if } S_i = \text{Positive} \\ \end{cases}$$

## Citation
If you find this work useful, please cite our paper:
```bib
@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",
    abstract = "The analysis of consumer sentiment, as expressed through reviews, can provide a wealth of insight regarding the quality of a product. While the study of sentiment analysis has been widely explored in many popular languages, relatively less attention has been given to the Bangla language, mostly due to a lack of relevant data and cross-domain adaptability. To address this limitation, we present BanglaBook, a large-scale dataset of Bangla book reviews consisting of 158,065 samples classified into three broad categories: positive, negative, and neutral. We provide a detailed statistical analysis of the dataset and employ a range of machine learning models to establish baselines including SVM, LSTM, and Bangla-BERT. Our findings demonstrate a substantial performance advantage of pre-trained models over models that rely on manually crafted features, emphasizing the necessity for additional training resources in this domain. Additionally, we conduct an in-depth error analysis by examining sentiment unigrams, which may provide insight into common classification errors in under-resourced languages like Bangla. Our codes and data are publicly available at https://github.com/mohsinulkabir14/BanglaBook.",
}
```