# Quantifying Political Bias in News Articles

arXiv: https://arxiv.org/abs/2210.03404 · HTML: https://mlsanity.com/paper/2210.03404/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 17 references that are in the map.
- First posted on arXiv 7 Oct 2022.

## Builds on (most cited first, 1 of 1)

- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)

## Built on by (most cited first, 3 of 3)

- [MN-DS: A Multilabeled News Dataset for News Articles Hierarchical Classification](https://mlsanity.com/paper/2212.12061/) (2022)
- [Mapping the Media Landscape: Predicting Factual Reporting and Political Bias Through Web Interactions](https://mlsanity.com/paper/2410.17655/) (2024)
- [An evaluation of LLMs for political bias in Western media: Israel-Hamas and Ukraine-Russia wars](https://mlsanity.com/paper/2601.06132/) (2026)

## Abstract (arXiv)

Search bias analysis is getting more attention in recent years since search results could affect In this work, we aim to establish an automated model for evaluating ideological bias in online news articles. The dataset is composed of news articles in search results as well as the newspaper articles. The current automated model results show that model capability is not sufficient to be exploited for annotating the documents automatically, thereby computing bias in search results.