language:ind aspect-based-sentiment-analysis region:us
HoASA: An aspect-based sentiment analysis dataset consisting of hotel reviews collected from the hotel aggregator platform, AiryRooms.
The dataset covers ten different aspects of hotel quality. Similar to the CASA dataset, each review is labeled with a single sentiment label for each aspect.
There are four possible sentiment classes for each sentiment label:
positive, negative, neutral, and positive-negative.
The positivenegative label is given to a review that contains multiple sentiments of the same aspect but for different objects (e.g., cleanliness of bed and toilet).
@inproceedings{azhar2019multi,
  title={Multi-label Aspect Categorization with Convolutional Neural Networks and Extreme Gradient Boosting},
  author={A. N. Azhar, M. L. Khodra, and A. P. Sutiono}
  booktitle={Proceedings of the 2019 International Conference on Electrical Engineering and Informatics (ICEEI)},
  pages={35--40},
  year={2019}
}
---
tags:
- aspect-based-sentiment-analysis
language:
- ind
---

# hoasa

HoASA: An aspect-based sentiment analysis dataset consisting of hotel reviews collected from the hotel aggregator platform, AiryRooms.

The dataset covers ten different aspects of hotel quality. Similar to the CASA dataset, each review is labeled with a single sentiment label for each aspect.

There are four possible sentiment classes for each sentiment label:

positive, negative, neutral, and positive-negative.

The positivenegative label is given to a review that contains multiple sentiments of the same aspect but for different objects (e.g., cleanliness of bed and toilet).

## Dataset Usage

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

## Citation

```
@inproceedings{azhar2019multi,
  title={Multi-label Aspect Categorization with Convolutional Neural Networks and Extreme Gradient Boosting},
  author={A. N. Azhar, M. L. Khodra, and A. P. Sutiono}
  booktitle={Proceedings of the 2019 International Conference on Electrical Engineering and Informatics (ICEEI)},
  pages={35--40},
  year={2019}
}
```

## License

CC-BY-SA 4.0

## 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)