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