Do You Think It's Biased? How To Ask For The Perception Of Media Bias
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Abstract (arXiv)
Media coverage possesses a substantial effect on the public perception of events. The way media frames events can significantly alter the beliefs and perceptions of our society. Nevertheless, nearly all media outlets are known to report news in a biased way. While such bias can be introduced by altering the word choice or omitting information, the perception of bias also varies largely depending on a reader's personal background. Therefore, media bias is a very complex construct to identify and analyze. Even though media bias has been the subject of many studies, previous assessment strategies are oversimplified, lack overlap and empirical evaluation. Thus, this study aims to develop a scale that can be used as a reliable standard to evaluate article bias. To name an example: Intending to measure bias in a news article, should we ask, "How biased is the article?" or should we instead ask, "How did the article treat the American president?". We conducted a literature search to find 824 relevant questions about text perception in previous research on the topic. In a multi-iterative process, we summarized and condensed these questions semantically to conclude a complete and representative set of possible question types about bias. The final set consisted of 25 questions with varying answering formats, 17 questions using semantic differentials, and six ratings of feelings. We tested each of the questions on 190 articles with overall 663 participants to identify how well the questions measure an article's perceived bias. Our results show that 21 final items are suitable and reliable for measuring the perception of media bias. We publish the final set of questions on http://bias-question-tree.gipplab.org/.
Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). Builds on 4 of its 41 references that are in the map. First posted on arXiv 14 Dec 2021.
Builds on
4 of 41 references.
References · 4
- 2019In Plain Sight: Media Bias Through the Lens of Factual Reportingcited by 68
- 2020Analyzing Political Bias and Unfairness in News Articles at Different Levels of Granularitycited by 32
- 2021MBIC -- A Media Bias Annotation Dataset Including Annotator Characteristicscited by 24
- 2021Enabling News Consumers to View and Understand Biased News Coverage: A Study on the Perception and Visualization of Media Biascited by 14
Built on by
Citing papers per year: 2021: 1; 2022: 4; 2023: 3; 2024: 2; 2025: 1; 2026: 1.
12 papers.
- 2022Neural Media Bias Detection Using Distant Supervision With BABE -- Bias Annotations By Expertscited by 56
- 2022NeuS: Neutral Multi-News Summarization for Mitigating Framing Biascited by 27
- 2022A Domain-adaptive Pre-training Approach for Language Bias Detection in Newscited by 16
- 2024The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detectioncited by 15
- 2023The Media Bias Taxonomy: A Systematic Literature Review on the Forms and Automated Detection of Media Biascited by 12
- 2022Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articlescited by 11
- 2021An Interdisciplinary Approach for the Automated Detection and Visualization of Media Bias in News Articlescited by 6
- 2024MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressionscited by 4
- 2023Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlinescited by 1
- 2023Mitigating Framing Bias with Polarity Minimization Losscited by 1
- 2025Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Marketscited by 0
- 2026Definitional Sensitivity in Media Bias Detection: A Multi-Definition Dataset and Benchmarkcited by 0
- 2026Definitional Sensitivity in Media Bias Detection: A Multi-Definition Dataset and Benchmark24 Aug 2026
- 2025Through the LLM Looking Glass: A Socratic Probing of Donkeys, Elephants, and Markets20 Mar 2025
- 2024The Promises and Pitfalls of LLM Annotations in Dataset Labeling: a Case Study on Media Bias Detection17 Nov 2024
- 2024MAGPIE: Multi-Task Media-Bias Analysis Generalization for Pre-Trained Identification of Expressions27 Feb 2024
- 2023The Media Bias Taxonomy: A Systematic Literature Review on the Forms and Automated Detection of Media Bias26 Dec 2023
- 2023Mitigating Framing Bias with Polarity Minimization Loss3 Nov 2023
- 2023Bias or Diversity? Unraveling Fine-Grained Thematic Discrepancy in U.S. News Headlines28 Mar 2023
- 2022Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articles7 Nov 2022
- 2022Neural Media Bias Detection Using Distant Supervision With BABE -- Bias Annotations By Experts29 Sep 2022
- 2022A Domain-adaptive Pre-training Approach for Language Bias Detection in News22 May 2022
- 2022NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias11 Apr 2022
- 2021An Interdisciplinary Approach for the Automated Detection and Visualization of Media Bias in News Articles26 Dec 2021