---
license: apache-2.0
tags:
- information-verification
- fact-checking
- fake-news-detection
pretty_name: >-
  Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions
size_categories:
- 1K<n<10K
---

# Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions

Dataset introduced in the paper ["Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions"](https://arxiv.org/abs/2410.17655) published in the CLEF 2024 main conference.

The dataset consists of a collections of **4K new media domains names with political bias and factual reporting labels**.

Columns of the dataset:
- `source`: domain name
- `bias`: the political bias label. Values: "left", "left-center", "neutral", "right-center", "right".
- `factual_reporting`: the factual reporting label. Values: "low", "mixed", "high".

**Github repo** released along with the paper [here](https://github.com/idiap/Factual-Reporting-and-Political-Bias-Web-Interactions).

## Load Training Dataset

```python
from datasets import load_dataset

dataset = load_dataset('sergioburdisso/news_media_bias_and_factuality')

print(dataset)
```
Output:
```python
DatasetDict({
    train: Dataset({
        features: ['source', 'bias', 'factual_reporting'],
        num_rows: 3920
    })
})
```

## Citation

Springer Paper: [here](https://link.springer.com/chapter/10.1007/978-3-031-71736-9_7).

```bibtex
@inproceedings{sanchez2024mapping,
  title={Mapping the media landscape: predicting factual reporting and political bias through web interactions},
  author={S{\'a}nchez-Cort{\'e}s, Dairazalia and Burdisso, Sergio and Villatoro-Tello, Esa{\'u} and Motlicek, Petr},
  booktitle={International Conference of the Cross-Language Evaluation Forum for European Languages},
  pages={127--138},
  year={2024},
  organization={Springer}
}
```

## License

Copyright (c) 2024 [Idiap Research Institute](https://www.idiap.ch/).
Apache 2.0 License.