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Experiments in News Bias Detection with Pre-Trained Neural Transformers

2024/06/14 by Tim Menzner, Menzner, Tim, Jochen L. Leidner +1
Social Sciences · Computer Science · #Misinformation and Its Impacts #Topic Modeling #Anomaly Detection Techniques and Applications

paper · doi:10.48550/arxiv.2406.09938

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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