sergioburdisso
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README.md
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license: apache-2.0
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---
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license: apache-2.0
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tags:
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- information-verification
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- fact-checking
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- fake-news-detection
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pretty_name: >-
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Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions
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size_categories:
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- 1K<n<10K
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---
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# Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions
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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.
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The dataset consists of a collections of **4K new media domains names with political bias and factual reporting labels**.
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Columns of the dataset:
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- `source`: domain name
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- `bias`: the political bias label. Values: "left", "left-center", "neutral", "right-center", "right".
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- `factual_reporting`: the factual reporting label. Values: "low", "mixed", "high".
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**Github repo** released along with the paper [here](https://github.com/idiap/Factual-Reporting-and-Political-Bias-Web-Interactions).
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## Load Training Dataset
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```python
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from datasets import load_dataset
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dataset = load_dataset('sergioburdisso/news_media_bias_and_factuality')
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print(dataset)
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```
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Output:
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```python
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DatasetDict({
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train: Dataset({
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features: ['source', 'bias', 'factual_reporting'],
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num_rows: 3920
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})
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})
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```
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## Citation
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Springer Paper: [here](https://link.springer.com/chapter/10.1007/978-3-031-71736-9_7).
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```bibtex
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@inproceedings{sanchez2024mapping,
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title={Mapping the media landscape: predicting factual reporting and political bias through web interactions},
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author={S{\'a}nchez-Cort{\'e}s, Dairazalia and Burdisso, Sergio and Villatoro-Tello, Esa{\'u} and Motlicek, Petr},
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booktitle={International Conference of the Cross-Language Evaluation Forum for European Languages},
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pages={127--138},
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year={2024},
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organization={Springer}
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}
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```
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## License
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Copyright (c) 2024 [Idiap Research Institute](https://www.idiap.ch/).
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Apache 2.0 License.
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