language:ind emotion-classification region:us
EmoT is an emotion classification dataset collected from the social media platform Twitter. The dataset consists of around 4000 Indonesian colloquial language tweets, covering five different emotion labels: anger, fear, happiness, love, and sadness.
EmoT dataset is splitted into 3 sets with 3521 train, 440 validation, 442 test data.
@inproceedings{saputri2018emotion,
  title={Emotion classification on indonesian twitter dataset},
  author={Saputri, Mei Silviana and Mahendra, Rahmad and Adriani, Mirna},
  booktitle={2018 International Conference on Asian Language Processing (IALP)},
  pages={90--95},
  year={2018},
  organization={IEEE}
}

@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:
- emotion-classification
language:
- ind
---

# emot

EmoT is an emotion classification dataset collected from the social media platform Twitter. The dataset consists of around 4000 Indonesian colloquial language tweets, covering five different emotion labels: anger, fear, happiness, love, and sadness.

EmoT dataset is splitted into 3 sets with 3521 train, 440 validation, 442 test data.

## Dataset Usage

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

## Citation

```
@inproceedings{saputri2018emotion,
  title={Emotion classification on indonesian twitter dataset},
  author={Saputri, Mei Silviana and Mahendra, Rahmad and Adriani, Mirna},
  booktitle={2018 International Conference on Asian Language Processing (IALP)},
  pages={90--95},
  year={2018},
  organization={IEEE}
}

@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)