Datasets:
Tasks:
Summarization
Sub-tasks:
news-articles-summarization
Languages:
English
Size Categories:
10K<n<100K
Source Datasets:
original
Tags:
License:
File size: 2,022 Bytes
6805151 e07cb85 6805151 9612395 6805151 9612395 6805151 9612395 59be645 9612395 6805151 e07cb85 fac94a2 e07cb85 |
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---
language:
- en
license:
- cc-by-nc-4.0
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
task_ids:
- news-articles-summarization
dataset_info:
features:
- name: text
dtype: string
- name: prediction
list:
- name: score
dtype: float64
- name: text
dtype: string
- name: prediction_agent
dtype: string
- name: annotation
dtype: 'null'
- name: annotation_agent
dtype: 'null'
- name: id
dtype: string
- name: metadata
dtype: 'null'
- name: status
dtype: string
- name: event_timestamp
dtype: timestamp[us]
- name: metrics
struct:
- name: text_length
dtype: int64
splits:
- name: train
num_bytes: 2563132.0446374374
num_examples: 1000
- name: test
num_bytes: 52331466.955362566
num_examples: 20417
download_size: 33207109
dataset_size: 54894599.0
---
# Dataset Card for "news-summary"
## Dataset Description
- **Homepage:** Kaggle Challenge
- **Repository:** https://www.kaggle.com/datasets/clmentbisaillon/fake-and-real-news-dataset?select=True.csv
- **Paper:** N.A.
- **Leaderboard:** N.A.
- **Point of Contact:** N.A.
### Dataset Summary
Officially it was supposed to be used for classification but, can you use this data set to summarize news articles?
### Languages
english
### Citation Information
Acknowledgements
Ahmed H, Traore I, Saad S. “Detecting opinion spams and fake news using text classification”, Journal of Security and Privacy, Volume 1, Issue 1, Wiley, January/February 2018.
Ahmed H, Traore I, Saad S. (2017) “Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques. In: Traore I., Woungang I., Awad A. (eds) Intelligent, Secure, and Dependable Systems in Distributed and Cloud Environments. ISDDC 2017. Lecture Notes in Computer Science, vol 10618. Springer, Cham (pp. 127-138).
### Contributions
Thanks to [@davidberenstein1957](https://github.com/davidberenstein1957) for adding this dataset. |