README.md

---
language:
- vi
task_categories:
- text-classification
task_ids:
- sentiment-classification
- topic-classification
pretty_name: fpt-comments-sentiment
license: other
size_categories:
- 1K<n<10K
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train.csv
  - split: test
    path: data/test.csv
---

# fpt-comments-sentiment

This is a hand-curated Vietnamese feedback dataset built from FPT-related discussions across Facebook communities, FuOverflow, Reddit/VOZ-style forums, FPT web pages, and other student-community sources. (Inspired by the NEU-ESC dataset)

The data is curated by manually collected examples with Facebook group comments scraped using Playwright, then cleaned, redacted, hand-reviewed, and labeled with support from LLM-assisted review.

Each row contains a redacted comment with two labels: one for sentiment and one for topic. The dataset is intended for Vietnamese sentiment analysis, toxicity detection, and community-topic classification in FPT University contexts.

*This dataset is created solely for use within the FPT coursework.*

## Sources

The data was manually curated from FPT-related public/community sources, including Facebook pages/groups, Reddit, VOZ, FuOverflow, and other FPT-related websites.

Source links include:

- Facebook group scrape source: https://www.facebook.com/groups/1775830216603784/
- Đại học FPT Hà Nội Facebook page: https://www.facebook.com/DaihocFPTHaNoi/
- FuOverflow Community: https://fuoverflow.com/
- Reddit r/vozforums: https://www.reddit.com/r/vozforums/
- VOZ forum: https://voz.vn/
- ... (and others)

Raw per-comment URLs, author/profile URLs, post URLs, permalinks, and scrape IDs are not included in the released CSV files.

## Data Files

Default splits:

- `data/train.csv`
- `data/test.csv`

Convenience full export:

- `data/all.csv`

Each CSV has:

- `Text`
- `Sentiment`
- `Classification`

## Labels

Sentiment:

- `0`: Neutral
- `1`: Positive
- `2`: Negative
- `3`: Toxic

Classification:

- `0`: Spam
- `1`: News
- `2`: Academic
- `3`: Other
- `4`: Service
- `5`: Jobs & Recruitment
- `6`: Personal Affairs
- `7`: Social Affairs
- `8`: Help & Share
- `9`: Club & Events

## Splits

| Split | Rows |
| --- | ---: |
| Train | 4,377 |
| Test | 1,092 |
| Total | 5,469 |

## Label Counts

Sentiment:

| Label | Rows |
| --- | ---: |
| Neutral | 2,974 |
| Positive | 1,380 |
| Negative | 1,067 |
| Toxic | 48 |

Classification:

| Label | Rows |
| --- | ---: |
| Spam | 70 |
| News | 16 |
| Academic | 1,912 |
| Other | 2,057 |
| Service | 491 |
| Jobs & Recruitment | 165 |
| Personal Affairs | 121 |
| Social Affairs | 107 |
| Help & Share | 442 |
| Club & Events | 88 |

## Notes

The text was redacted before export. The CSV files do not include raw author names, profile URLs, post URLs, permalinks, response URLs, or scrape IDs.

Angle-bracket placeholders are used for redaction; starred masks were normalized to context placeholders such as `<NAME>`.

Toxic labels are intended for targeted abuse, insults, slurs, hostile commands, or similar direct attacks. Profanity alone was not treated as toxic.


## Citation

If you use the label schema/protocol inspired by NEU-ESC, please cite:

```bibtex
@misc{mai2025neuesc,
  title = {NEU-ESC: A Comprehensive Vietnamese dataset for Educational Sentiment analysis and topic Classification toward multitask learning},
  author = {Mai, Phan Quoc Hung and Nguyen, Quang Hung and Duong, Phuong Giang and Nguyen, Hong Hanh and Long, Nguyen Tuan},
  year = {2025},
  eprint = {2506.23524},
  archivePrefix = {arXiv},
  primaryClass = {cs.CL},
  doi = {10.48550/arXiv.2506.23524},
  url = {https://arxiv.org/abs/2506.23524}
}
```