Bias-Mitigating News Search with BiasRank

Tim Menzner, Jochen Leidner, Jochen Leidner

2025

Abstract

As geopolitical adversaries as well as internal commercial and political actors target democracies with disinformation campaigns, it is increasingly necessary to filter out biased reporting. Some automatic success has recently been achieved in this task. For further progress, web search engines need to implement news bias resistance mechanisms for ranking news stories. To this end, we present BiasRank, a new approach that demotes articles exhibiting news media bias by combining a large neural language model for news bias classification with a heuristic re-ranker. Our experiments, based on artificially polluting a (mostly neutral) standard news corpus with various degrees of biased news stories (biased to varying extents), inspired by earlier work on answer injection, demonstrate the effectiveness of the approach. Our evaluation shows that the method radically reduces news bias at a negligible cost in terms of relevance. In turn, we also provide new metrics for the evaluation of similar systems that aim to balance two variables (like relevancy and bias in our case). Additionally, we release our test collection on git to support further research on de-biasing news search.

Paper Citation

in Harvard Style

Menzner T. and Leidner J. (2025). Bias-Mitigating News Search with BiasRank. In Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR; ISBN , SciTePress, pages 436-447. DOI: 10.5220/0013755200004000

in Bibtex Style

@conference{kdir25,
author={Tim Menzner and Jochen Leidner},
title={Bias-Mitigating News Search with BiasRank},
booktitle={Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR},
year={2025},
pages={436-447},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013755200004000},
isbn={},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR
TI - Bias-Mitigating News Search with BiasRank
SN -
AU - Menzner T.
AU - Leidner J.
PY - 2025
SP - 436
EP - 447
DO - 10.5220/0013755200004000
PB - SciTePress