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---
task_categories:
- text-classification
language:
- vi
---
## Dataset Card for ViSpamReviews
### 1. Dataset Summary
**ViSpamReviews** is a Vietnamese e‑commerce review dataset for spam detection, with both:
* **Binary task**: `Label` ∈ {0 = non‑spam, 1 = spam}.
* **Multi‑class task**: `SpamLabel` ∈ {0 = NO-SPAM, 1 = SPAM-1 (fake review), 2 = SPAM-2 (brand‑only), 3 = SPAM-3 (irrelevant)}.
It collects reviews from major Vietnamese online shopping platforms, annotated via a strict procedure to identify deceptive or irrelevant content.
### 2. Supported Tasks and Metrics
* **Tasks**
* **Binary classification**: Is the review spam?
* **Multi‑class classification**: Type of spam review.
* **Metrics**
* **Binary**: Accuracy, macro F1
* **Multi‑class**: Accuracy, macro F1
On PhoBERT, the original achieves **86.89%** macro F1 on binary and **72.17%** macro F1 on multi‑class.
### 3. Languages
* Vietnamese
### 4. Dataset Structure
The unified CSV has these columns:
| Column | Type | Description |
| ----------- | ------ | ------------------------------------------------------------------- |
| `dataset` | string | Source identifier (always `ViSpamReviews` in this unified version). |
| `type` | string | Split: `train` / `validation` / `test`. |
| `comment` | string | The raw user review text. |
| `Label` | int | Binary spam flag: 0 = non‑spam, 1 = spam. |
| `SpamLabel` | int | Multi‑class label: 0=NO-SPAM, 1=SPAM-1, 2=SPAM-2, 3=SPAM-3. |
### 5. Data Fields
* **Comment** (`str`): The user's product review.
* **Label** (`int`): Binary spam label.
* **SpamLabel** (`int`): Spam type (0–3).
* **type** (`str`): Which split this example belongs to.
* **dataset** (`str`): Always `ViSpamReviews` for provenance.
### 6. Usage
```python
from datasets import load_dataset
ds = load_dataset("visolex/vispamreviews")
train = ds.filter(lambda ex: ex["type"] == "train")
val = ds.filter(lambda ex: ex["type"] == "dev")
test = ds.filter(lambda ex: ex["type"] == "test")
print(train[0])
```
### 7. Source & Links
* **GitHub (original code & raw data)**
[https://github.com/sonlam1102/vispamdetection](https://github.com/sonlam1102/vispamdetection)
* **Original Paper**
Van Dinh et al. (2022), “Detecting Spam Reviews on Vietnamese E‑Commerce Websites” ([arxiv.org][1])
---
### 8. Licensing and Citation
#### License
Refer to the GitHub repo’s LICENSE. If unspecified, assume **CC BY 4.0**.
#### How to Cite
```bibtex
@InProceedings{10.1007/978-3-031-21743-2_48,
author = {Van Dinh, Co and Luu, Son T. and Nguyen, Anh Gia-Tuan},
title = {Detecting Spam Reviews on Vietnamese E-Commerce Websites},
booktitle = {Intelligent Information and Database Systems},
year = {2022},
publisher = {Springer International Publishing},
pages = {595--607},
isbn = {978-3-031-21743-2}
}
@misc{sonlam1102_vispamdetection,
title = {ViSpamReviews: Spam Reviews Detection on Vietnamese E‑Commerce},
author = {{sonlam1102}},
howpublished = {\url{https://github.com/sonlam1102/vispamdetection}},
year = {2022}
}
``` |