Experiments in News Bias Detection with Pre-Trained Neural Transformers
<|reference_start|>Experiments in News Bias Detection with Pre-Trained Neural Transformers: The World Wide Web provides unrivalled access to information globally, including factual news reporting and commentary. However, state actors and commercial players increasingly spread biased (distorted) or fake (non-factual) information to promote their agendas. We compare several large, pre-trained language models on the task of sentence-level news bias detection and sub-type classification, providing quantitative and qualitative results.<|reference_end|>
@article{menzner2024experiments,
    title={Experiments in News Bias Detection with Pre-Trained Neural Transformers},
    author={Tim Menzner, Jochen L. Leidner},
    journal={arXiv preprint arXiv:2406.09938},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.09938},
    primaryClass={cs.CL cs.AI}
}