sergioburdisso/news_media_reliability

Reliability Estimation of News Media Sources: "Birds of a Feather Flock Together"

Dataset introduced in the paper "Reliability Estimation of News Media Sources: Birds of a Feather Flock Together" published in the NAACL 2024 main conference.

Similar to the news media bias and factual reporting dataset, this dataset consists of a collections of 5.33K new media domains names with reliability labels. Additionally, for some domains, there is also a human-provided reliability score available.

Columns of the dataset:

• domain: domain name
• reliability_label: the reliability label. Values:
  • 1: generally reliable;
  • 0: mixed;
  • -1: generally unreliable
• newsguard_score: human-provided reliability score (only available for a small subset). Value: integer number between 0 and 100.

Github repo released along with the paper here.

Load Training Dataset

from datasets import load_dataset

dataset = load_dataset('sergioburdisso/news_media_reliability')

print(dataset)

Output:

DatasetDict({
    train: Dataset({
        features: ['domain', 'reliability_label', 'newsguard_score'],
        num_rows: 5332
    })
})

Citation

NAACL Paper: here.

@inproceedings{burdisso-etal-2024-reliability,
    title = "Reliability Estimation of News Media Sources: Birds of a Feather Flock Together",
    author = "Burdisso, Sergio  and
      Sanchez-cortes, Dairazalia  and
      Villatoro-tello, Esa{\'u}  and
      Motlicek, Petr",
    editor = "Duh, Kevin  and
      Gomez, Helena  and
      Bethard, Steven",
    booktitle = "Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = jun,
    year = "2024",
    address = "Mexico City, Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.naacl-long.383",
    pages = "6893--6911",
}

License

Copyright (c) 2024 Idiap Research Institute.

Apache 2.0 License.