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@@ -1,53 +1,48 @@
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  ---
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  language:
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- - zh
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  license: mit
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  pretty_name: RedNote Covert Advertisement Detection Dataset
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  tags:
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- - covert advertisement detection
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- - social-media
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- - image-text
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- - multimodal
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- - RedNote
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- - Xiaohongshu
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  datasets:
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- - Jingyi77/CHASM-Covert_Advertisement_on_RedNote
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  dataset_info:
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- - config_name: default
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- features:
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- - name: id
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- dtype: string
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- - name: title
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- dtype: string
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- - name: description
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- dtype: string
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- - name: date
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- dtype: string
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- - name: comments
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- sequence:
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- dtype: string
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- - name: images
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- sequence:
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- dtype: string
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- - name: image_count
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- dtype: int32
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- - name: label
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- dtype: int8
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- - name: split
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- dtype: string
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  configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: train.parquet
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- - split: test
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- path: test.parquet
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- - split: validation
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- path: val.parquet
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  size_categories:
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- - 1K<n<10K
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- task_categories:
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- - text-classification
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  ---
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  <!-- @format -->
@@ -65,16 +60,18 @@ This dataset contains posts from the RedNote platform for covert advertisement d
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  | Test | 1000 | 130 | 870 | 5103 |
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  | **Total** | **4992** | **613** | **4379** | **26324** |
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  ## Field Descriptions
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- Each parquet file contains the following fields:
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  - `id`: Unique identifier for each post
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  - `title`: Post title
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  - `description`: Post description content
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  - `date`: Publication date (format: MM-DD)
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  - `comments`: List of comments
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- - `images`: List of images paths
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  - `image_count`: Number of images
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  - `label`: Label (0=non-advertisement, 1=advertisement)
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  - `split`: Data split (train/validation/test)
@@ -87,7 +84,7 @@ Each parquet file contains the following fields:
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  ## Data Format
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- The dataset is stored in WebDataset format, with each sample containing:
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  1. One or more image files (.jpg format)
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  2. A JSON metadata file with the following fields:
@@ -103,17 +100,11 @@ The dataset is stored in WebDataset format, with each sample containing:
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  ```python
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  from datasets import load_dataset
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- # Load training set
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- train_dataset = load_dataset("Jingyi77/CHASM-Covert_Advertisement_on_RedNote", split="train")
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-
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- # Load validation set
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- val_dataset = load_dataset("Jingyi77/CHASM-Covert_Advertisement_on_RedNote", split="validation")
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-
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- # Load test set
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- test_dataset = load_dataset("Jingyi77/CHASM-Covert_Advertisement_on_RedNote", split="test")
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  # Access a sample
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- example = train_dataset[0]
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  metadata = {
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  "id": example["id"],
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  "title": example["title"],
@@ -136,4 +127,4 @@ If you use this dataset in your research, please cite:
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  journal = {Hugging Face Hub},
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  howpublished = {\url{https://huggingface.co/datasets/Jingyi77/CHASM-Covert_Advertisement_on_RedNote}}
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  }
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- ```
 
1
  ---
2
  language:
3
+ - zh
4
  license: mit
5
  pretty_name: RedNote Covert Advertisement Detection Dataset
6
  tags:
7
+ - covert advertisement detection
8
+ - social-media
9
+ - image-text
10
+ - multimodal
11
+ - RedNote
12
+ - Xiaohongshu
13
  datasets:
14
+ - Jingyi77/CHASM-Covert_Advertisement_on_RedNote
15
  dataset_info:
16
+ - config_name: default
17
+ features:
18
+ - name: id
19
+ dtype: string
20
+ - name: title
21
+ dtype: string
22
+ - name: description
23
+ dtype: string
24
+ - name: date
25
+ dtype: string
26
+ - name: comments
27
+ sequence:
28
+ dtype: string
29
+ - name: images
30
+ sequence:
31
+ dtype: string
32
+ - name: image_count
33
+ dtype: int32
34
+ - name: label
35
+ dtype: int8
36
+ - name: split
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+ dtype: string
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  configs:
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+ - config_name: default
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+ data_files:
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+ - split: default
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+ path: example.parquet
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+
 
 
 
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  size_categories:
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+ - 10<n<100
 
 
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  ---
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  <!-- @format -->
 
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  | Test | 1000 | 130 | 870 | 5103 |
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  | **Total** | **4992** | **613** | **4379** | **26324** |
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+ > 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.
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+
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  ## Field Descriptions
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+ The example parquet file contains the following fields:
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  - `id`: Unique identifier for each post
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  - `title`: Post title
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  - `description`: Post description content
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  - `date`: Publication date (format: MM-DD)
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  - `comments`: List of comments
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+ - `images`: List of base64-encoded images
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  - `image_count`: Number of images
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  - `label`: Label (0=non-advertisement, 1=advertisement)
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  - `split`: Data split (train/validation/test)
 
84
 
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  ## Data Format
86
 
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+ The complete dataset is stored in WebDataset format, with each sample containing:
88
 
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  1. One or more image files (.jpg format)
90
  2. A JSON metadata file with the following fields:
 
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  ```python
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  from datasets import load_dataset
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+ # Load example dataset
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+ dataset = load_dataset("Jingyi77/CHASM-Covert_Advertisement_on_RedNote")
 
 
 
 
 
 
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  # Access a sample
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+ example = dataset[0]
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  metadata = {
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  "id": example["id"],
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  "title": example["title"],
 
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  journal = {Hugging Face Hub},
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  howpublished = {\url{https://huggingface.co/datasets/Jingyi77/CHASM-Covert_Advertisement_on_RedNote}}
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  }
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+ ```