On the nature of real and perceived bias in the mainstream media
Open accessAbstract
News consumers expect news outlets to be objective and balanced in their reports of events and opinions. However, there is a growing body of evidence of bias in the media caused by underlying political and socio-economic viewpoints. Previous studies have tried to classify the partiality of the media, but there is little work on quantifying it, and less still on the nature of this partiality. The vast amount of content published in social media enables us to quantify the inclination of the press to pre-defined sides of the socio-political spectrum. To describe such tendencies, we use tweets to automatically compute a news outlet's political and socio-economic orientation. Results show that the media have a measurable bias, and illustrate this by showing the favoritism of Chilean media for the ruling political parties in the country. This favoritism becomes clearer as we empirically observe a shift in the position of the mass media when there is a change in government. Even though relative differences in bias between news outlets can be observed, public awareness of the bias of the media landscape as a whole appears to be limited by the political space defined by the news that we receive as a population. We found that the nature of the bias is reflected in the vocabulary used and the entities mentioned by different news outlets. A survey conducted among news consumers confirms that media bias has an impact on the coverage of controversial topics and that this is perceivable by the general audience. Having a more accurate method to measure and characterize media bias will help readers position outlets in the socio-economic landscape, even when a (sometimes opposite) self-declared position is stated. This will empower readers to better reflect on the content provided by their news outlets of choice.
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The proposed computational models classify the partiality of media sources without quantifying their ideology.
“The proposed computational models classify the partiality of media sources without quantifying their ideology (Elejalde et al., 2018).”
From Political Ideology and Polarization: A Multi-dimensional Approach (2022) · cites this paper as Elejalde et al., 2018
The Related work section says the authors propose a methodology that quantifies news outlets’ political leaning, contrary to the claim that their proposed model does not quantify ideology. The Abstract likewise says they automatically compute outlets’ political and socio-economic orientation. Although it says earlier studies often classified partiality without quantifying it, that does not describe this paper’s proposed method; page numbers were not provided in our copy. (LLM, conf=0.87)
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Cites
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“In this sense, we could benefit from advances in systems that focus on identifying controversial topics in social media [54].”
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Sorted by citations
Political Ideology and Polarization: A Multi-dimensional Approach
Sinno, B., Oviedo, B., Atwell, K., Alikhani, M., & Li, J. J. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2022.naacl-main.17 · Cited by 12 · see citing works
“The proposed computational models classify the partiality of media sources without quantifying their ideology (Elejalde et al., 2018).”
Background
- Authors
- Elejalde, E., Ferres, L., & Herder, E.
- Affiliations
- University of Concepción (CL)
- Universidad del Desarrollo (CL)
- Radboud University Nijmegen (NL)
- Corresponding author
- Elejalde, Erick
- Ferres, Leo
- Venue
- PLOS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-03-23
- Volume
- 13
- Issue
- 3
- Pages
- e0193765
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC5865717
- OpenAlex
- W2793539342
- Cited by
- 64
- References
- 2
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 6 · 2023: 6 · 2022: 3 · 2021: 8 · 2020: 11 · 2019: 6 · 2018: 5
- FWCI
- 17.06
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Radboud Repository (Radboud University) (submittedVersion)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Funders
- Comisión Nacional de Investigación Científica y Tecnológica (63130228)
- Topics
- Social Sciences › Sociology and Political Science › Media Influence and Politics
- Social Sciences › Communication › Media Studies and Communication
- Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
- Keywords
- media bias, mainstream media, tweets, Chilean media, government change, perceived bias, news consumers, controversial issues, political vocabulary
- MeSH terms
- Awareness, Chile, Economics, Humans, Mass Media, Pattern Recognition, Automated, Politics, Prejudice, Psychological Tests, Social Perception, Social Media
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