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

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

@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}
}