language:ind sentiment-analysis region:us
SmSA is a sentence-level sentiment analysis dataset (Purwarianti and Crisdayanti, 2019) is a collection of comments and reviews
in Indonesian obtained from multiple online platforms. The text was crawled and then annotated by several Indonesian linguists
to construct this dataset. There are three possible sentiments on the SmSA dataset: positive, negative, and neutral
@INPROCEEDINGS{8904199,
    author={Purwarianti, Ayu and Crisdayanti, Ida Ayu Putu Ari},
    booktitle={2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)},
    title={Improving Bi-LSTM Performance for Indonesian Sentiment Analysis Using Paragraph Vector},
    year={2019},
    pages={1-5},
    doi={10.1109/ICAICTA.2019.8904199}
}

@inproceedings{wilie2020indonlu,
  title={IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding},
  author={Wilie, Bryan and Vincentio, Karissa and Winata, Genta Indra and Cahyawijaya, Samuel and Li, Xiaohong and Lim, Zhi Yuan and Soleman, Sidik and Mahendra, Rahmad and Fung, Pascale and Bahar, Syafri and others},
  booktitle={Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing},
  pages={843--857},
  year={2020}
}
---
tags:
- sentiment-analysis
language:
- ind
---

# smsa

SmSA is a sentence-level sentiment analysis dataset (Purwarianti and Crisdayanti, 2019) is a collection of comments and reviews

in Indonesian obtained from multiple online platforms. The text was crawled and then annotated by several Indonesian linguists

to construct this dataset. There are three possible sentiments on the SmSA dataset: positive, negative, and neutral

## Dataset Usage

Run `pip install nusacrowd` before loading the dataset through HuggingFace's `load_dataset`.

## Citation

```
@INPROCEEDINGS{8904199,
    author={Purwarianti, Ayu and Crisdayanti, Ida Ayu Putu Ari},
    booktitle={2019 International Conference of Advanced Informatics: Concepts, Theory and Applications (ICAICTA)},
    title={Improving Bi-LSTM Performance for Indonesian Sentiment Analysis Using Paragraph Vector},
    year={2019},
    pages={1-5},
    doi={10.1109/ICAICTA.2019.8904199}
}

@inproceedings{wilie2020indonlu,
  title={IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding},
  author={Wilie, Bryan and Vincentio, Karissa and Winata, Genta Indra and Cahyawijaya, Samuel and Li, Xiaohong and Lim, Zhi Yuan and Soleman, Sidik and Mahendra, Rahmad and Fung, Pascale and Bahar, Syafri and others},
  booktitle={Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing},
  pages={843--857},
  year={2020}
}
```

## License

Creative Commons Attribution Share-Alike 4.0 International

## Homepage

[https://github.com/IndoNLP/indonlu](https://github.com/IndoNLP/indonlu)

### NusaCatalogue

For easy indexing and metadata: [https://indonlp.github.io/nusa-catalogue](https://indonlp.github.io/nusa-catalogue)