File size: 1,071 Bytes
fc85d5b b8c5b9f fc85d5b b8c5b9f f9d1fe1 b8c5b9f f9d1fe1 edeea39 b8c5b9f f9d1fe1 b8c5b9f f9d1fe1 b8c5b9f dfe7006 b8c5b9f b4a8ae9 fd55107 b83b25b b4a8ae9 b83b25b b4a8ae9 b83b25b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
---
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 |