|
--- |
|
language: |
|
- zh |
|
license: mit |
|
pretty_name: RedNote Covert Advertisement Detection Dataset |
|
tags: |
|
- covert advertisement detection |
|
- social-media |
|
- image-text |
|
- multimodal |
|
- RedNote |
|
- Xiaohongshu |
|
datasets: |
|
- Jingyi77/CHASM-Covert_Advertisement_on_RedNote |
|
dataset_info: |
|
- config_name: default |
|
features: |
|
- name: id |
|
dtype: string |
|
- name: title |
|
dtype: string |
|
- name: description |
|
dtype: string |
|
- name: date |
|
dtype: string |
|
- name: comments |
|
sequence: |
|
dtype: string |
|
- name: images |
|
sequence: |
|
dtype: string |
|
- name: image_count |
|
dtype: int32 |
|
- name: label |
|
dtype: int8 |
|
- name: split |
|
dtype: string |
|
configs: |
|
- config_name: Example |
|
data_files: |
|
- split: Example |
|
path: example.parquet |
|
- split: Train_1 |
|
path: train_part_1.parquet |
|
- split: Train_2 |
|
path: train_part_2.parquet |
|
- split: Train_3 |
|
path: train_part_3.parquet |
|
- split: Train_4 |
|
path: train_part_4.parquet |
|
- split: Test |
|
path: test.parquet |
|
- split: Validation |
|
path: validation.parquet |
|
size_categories: |
|
- 10<n<100 |
|
--- |
|
|
|
<!-- @format --> |
|
|
|
# RedNote Covert Advertisement Detection Dataset |
|
|
|
This dataset contains posts from the RedNote platform for covert advertisement detection tasks. |
|
|
|
## Dataset Overview |
|
|
|
| Split | Posts | Ad Posts | Non-Ad Posts | Total Images | |
|
| ---------- | -------- | -------- | ------------ | ------------ | |
|
| Train | 3493 | 426 | 3067 | 18543 | |
|
| Validation | 499 | 57 | 442 | 2678 | |
|
| Test | 1000 | 130 | 870 | 5103 | |
|
| **Total** | **4992** | **613** | **4379** | **26324** | |
|
|
|
> Note: The viewer shows a **small example subset** of the data (60 samples) for demonstration purposes. The complete dataset is available via WebDataset format in the repository. |
|
|
|
## Field Descriptions |
|
|
|
The example parquet file contains the following fields: |
|
|
|
- `id`: Unique identifier for each post |
|
- `title`: Post title |
|
- `description`: Post description content |
|
- `date`: Publication date (format: MM-DD) |
|
- `comments`: List of comments |
|
- `images`: List of base64-encoded images |
|
- `image_count`: Number of images |
|
- `label`: Label (0=non-advertisement, 1=advertisement) |
|
- `split`: Data split (train/validation/test) |
|
|
|
## Dataset Features |
|
|
|
- **Multimodal Data**: Each post contains both text (title, description, comments) and images |
|
- **Real-world Data**: Collected from actual social media posts on the RedNote platform |
|
- **Multiple Images**: Each post may contain multiple images (average of 5.27 images per post) |
|
|
|
## Data Format |
|
|
|
The complete dataset is stored in WebDataset format, with each sample containing: |
|
|
|
1. One or more image files (.jpg format) |
|
2. A JSON metadata file with the following fields: |
|
- `id`: Sample ID |
|
- `title`: Title |
|
- `description`: Description |
|
- `date`: Date |
|
- `comments`: List of comments |
|
- `label`: Label (0: non-advertisement, 1: advertisement) |
|
|
|
## Loading the Dataset |
|
|
|
```python |
|
from datasets import load_dataset |
|
|
|
# Load example dataset |
|
dataset = load_dataset("Jingyi77/CHASM-Covert_Advertisement_on_RedNote") |
|
|
|
# Access a sample |
|
example = dataset[0] |
|
metadata = { |
|
"id": example["id"], |
|
"title": example["title"], |
|
"description": example["description"], |
|
"label": example["label"] |
|
} |
|
images = example["images"] # List of images |
|
``` |
|
|
|
## Citation |
|
|
|
If you use this dataset in your research, please cite: |
|
|
|
``` |
|
@dataset{CHASM, |
|
author = {Jingyi Zheng, Tianyi Hu, Yule Liu, Zhen Sun, Zongmin Zhang, Wenhan Dong, Zifan Peng, Xinlei He}, |
|
title = {CHASM: Unveiling Covert Advertisements on Chinese Social Media}, |
|
year = {2025}, |
|
publisher = {Hugging Face}, |
|
journal = {Hugging Face Hub}, |
|
howpublished = {\url{https://huggingface.co/datasets/Jingyi77/CHASM-Covert_Advertisement_on_RedNote}} |
|
} |
|
``` |
|
|