Update README.md

README.md

@@ -1,3 +1,107 @@
----
-license: mit
----
+---
+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}
+}
+
+```