|
--- |
|
language: |
|
- en |
|
license: apache-2.0 |
|
task_categories: |
|
- text-classification |
|
dataset_info: |
|
features: |
|
- name: text |
|
dtype: string |
|
- name: embeddings |
|
sequence: float32 |
|
- name: label |
|
dtype: int64 |
|
splits: |
|
- name: train |
|
num_bytes: 31661636 |
|
num_examples: 4487 |
|
- name: test |
|
num_bytes: 3527028 |
|
num_examples: 499 |
|
download_size: 30964782 |
|
dataset_size: 35188664 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
- split: test |
|
path: data/test-* |
|
--- |
|
|
|
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, validation, and test sets. |
|
|
|
- text: text of the article |
|
|
|
- label: a label that marks the article as potentially unreliable |
|
- 1: fake |
|
- 0: true |
|
|
|
Datasets Distribution: |
|
- Train: 70% |
|
- Val: 20% |
|
- Test: 10% |