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---
license: apache-2.0
tags:
- information-verification
- fact-checking
- fake-news-detection
pretty_name: >-
Reliability Estimation of News Media Sources: Birds of a Feather Flock
Together
size_categories:
- 1K<n<10K
---
# 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"](https://arxiv.org/abs/2404.09565) published in the NAACL 2024 main conference.
Similar to the [news media bias and factual reporting dataset](https://huggingface.co/datasets/sergioburdisso/news_media_bias_and_factuality), 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](https://github.com/idiap/News-Media-Reliability).
## Load Training Dataset
```python
from datasets import load_dataset
dataset = load_dataset('sergioburdisso/news_media_reliability')
print(dataset)
```
Output:
```python
DatasetDict({
train: Dataset({
features: ['domain', 'reliability_label', 'newsguard_score'],
num_rows: 5332
})
})
```
## Citation
NAACL Paper: [here](https://aclanthology.org/2024.naacl-long.383/).
```bibtex
@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](https://www.idiap.ch/).
Apache 2.0 License. |