Datasets:
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---
dataset_info:
features:
- name: ID
dtype: string
- name: Text
dtype: string
- name: Polarity
dtype: string
- name: Domain
dtype: string
splits:
- name: train
num_bytes: 15164685
num_examples: 70000
download_size: 7415117
dataset_size: 15164685
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- sentigold
- bangla
- bangladataset
- sentiment
---
# Bangla Sentiment Dataset (SentiGOLD v1)
**SentiGOLD 70k v1** A multi-domain sentiment analysis dataset in Bangla is called SentiGOLD. A gender-balanced team of linguists annotated the 70,000 samples, which were obtained from a variety of sources. SentiGOLD complies with language standards that have been developed by a Bangla linguistics commission and the Government of Bangladesh.
Each text entry in the dataset is categorized into one of the following sentiment classes:
- **SP**: Strongly Positive
- **WP**: Weakly Positive
- **WN**: Weakly Positive Negative
- **SN**: Strongly Negative
- **NU**: Neutral
This dataset provides a valuable resource for building and evaluating sentiment analysis models in the Bangla language.
## Use the Dataset
```python
from datasets import load_dataset
dataset = load_dataset('SayedShaun/sentigold')
print(dataset)
>>> DatasetDict({
>>> train: Dataset({
>>> features: ['ID', 'Text', 'Polarity', 'Domain'],
>>> num_rows: 70000
>>> })
>>> })
```
## Source and Citation
**[SentiGOLD: A Large Bangla Gold Standard Multi-Domain Sentiment Analysis Dataset and Its Evaluation](https://arxiv.org/abs/2306.06147)**
```bibtex
@inproceedings{islam2023sentigold,
title={Sentigold: A large bangla gold standard multi-domain sentiment analysis dataset and its evaluation},
author={Islam, Md Ekramul and Chowdhury, Labib and Khan, Faisal Ahamed and Hossain, Shazzad and Hossain, Md Sourave and Rashid, Mohammad Mamun Or and Mohammed, Nabeel and Amin, Mohammad Ruhul},
booktitle={Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
pages={4207--4218},
year={2023}
} |