metadata

language:
  - en
license:
  - cc-by-nc-4.0
size_categories:
  - 10K<n<100K
source_datasets:
  - original
task_categories:
  - text-classificat
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

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 for adding this dataset.