--- language: - zh license: mit size_categories: - 1K # RedNote Covert Advertisement Detection Dataset (CHASM) This dataset contains posts from the RedNote platform for covert advertisement detection tasks, introduced in the paper [CHASM: Unveiling Covert Advertisements on Chinese Social Media](https://huggingface.co/papers/2604.20511). [**Paper**](https://huggingface.co/papers/2604.20511) | [**Code**](https://github.com/Jingyi62/CHASM) ## 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: ```bibtex @article{zheng2025chasm, title={CHASM: Unveiling Covert Advertisements on Chinese Social Media}, author={Zheng, Jingyi and Hu, Tianyi and Liu, Yule and Sun, Zhen and Zhang, Zongmin and Dong, Wenhan and Peng, Zifan and He, Xinlei}, journal={arXiv preprint arXiv:2604.20511}, year={2025} } ```