Experiments in News Bias Detection with Pre-Trained Neural Transformers

Tim Menzner; Jochen L. Leidner

doi:10.1007/978-3-031-56066-8_22

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arXiv · 2406.09938

Experiments in News Bias Detection with Pre-Trained Neural Transformers

Tim Menzner·Jochen L. Leidner

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Abstract

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.

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Tim Menzner, Jochen L. Leidner. 2024-06-14. Experiments in News Bias Detection with Pre-Trained Neural Transformers. https://doi.org/10.1007/978-3-031-56066-8_22

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