| --- |
| language: |
| - en |
| license: apache-2.0 |
| task_categories: |
| - text-classification |
| dataset_info: |
| features: |
| - name: text |
| dtype: string |
| - name: label |
| dtype: int64 |
| - name: bert_embeddings |
| sequence: float32 |
| - name: roberta_embeddings |
| sequence: float32 |
| splits: |
| - name: train |
| num_bytes: 45378307 |
| num_examples: 4487 |
| - name: test |
| num_bytes: 5147293 |
| num_examples: 499 |
| download_size: 49990113 |
| dataset_size: 50525600 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: test |
| path: data/test-* |
| tags: |
| - fake-news |
| --- |
| |
| Dataset Source: [Fake News Detection Challenge KDD 2020](https://www.kaggle.com/competitions/fakenewskdd2020/data) |
|
|
| This is a copied and reformatted version of the Fake News Detection Challenge KDD 2020. |
|
|
| We use the raw `train.csv` from the official Kaggle Dataset and split the data into train and test sets. |
|
|
| - text: text of the article (str) |
| - embeddings: BERT embeddings (768, ) |
| - label: (int) |
| - 1: fake |
| - 0: true |
|
|
| Datasets Distribution: |
| - Train: 4487 |
| - Test: 499 |
