Improved Models for Media Bias Detection and Subcategorization

Tim Menzner, Jochen L. Leidner

Abstract:

We present improved models for the granular detection and
sub-classification news media bias in English news articles. We compare
the performance of zero-shot versus fine-tuned large pre-trained neural
transformer language models, explore how the level of detail of the classes
affects performance on a novel taxonomy of 27 news bias-types, and
demonstrate how using synthetically generated example data can be used
to improve quality.

Keywords: media bias· propaganda detection· content quality· news analysis· metadata enrichment· natural language processing