Cited by 336Media Influence and PoliticsNews Media Framing and Political CommunicationComputational and Text Analysis Methods

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Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis

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Budak, Ceren, Goel, Sharad, Rao, Justin M.·2016·Public Opinion Quarterly

DOI 10.1093/poq/nfw007

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Abstract

It is widely thought that news organizations exhibit ideological bias, but rigorously quantifying such slant has proven methodologically challenging. Through a combination of machine learning and crowdsourcing techniques, we investigate the selection and framing of political issues in 15 major U.S. news outlets. Starting with 803,146 news stories published over 12 months, we first used supervised learning algorithms to identify the 14% of articles pertaining to political events. We then recruited 749 online human judges to classify a random subset of 10,950 of these political articles according to topic and ideological position. Our analysis yields an ideological ordering of outlets consistent with prior work. We find, however, that news outlets are considerably more similar than generally believed. Specifically, with the exception of political scandals, we find that major news organizations present topics in a largely non-partisan manner, casting neither Democrats nor Republicans in a particularly favorable or unfavorable light. Moreover, again with the exception of political scandals, there is little evidence of systematic differences in story selection, with all major news outlets covering a wide variety of topics with frequency largely unrelated to the outlet's ideological position. Finally, we find that news organizations express their ideological bias not by directly advocating for a preferred political party, but rather by disproportionately criticizing one side, a con…

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Authors: Budak, C., Goel, S., & Rao, J. M.
Affiliations: Microsoft (United States) (US)
Corresponding author: Budak, Ceren
ORCID: Budak, Ceren
Goel, Sharad
Venue: Public Opinion Quarterly
Publisher: Oxford University Press (OUP)
Published: 2016
Volume: 80
Issue: S1
Pages: 250-271
ISSN: 0033-362X (ISSN-L)
1537-5331
DOI: 10.1093/poq/nfw007
OpenAlex: W1119807432
Cited by: 336
References: 52
Citations by year: 2026: 18 · 2025: 40 · 2024: 28 · 2023: 38 · 2022: 30 · 2021: 55 · 2020: 38 · 2019: 39 · 2018: 32 · 2017: 9 · 2016: 5
FWCI: 81.00
Type: journal article
Language: en
Open access: green
doi.org
Locations: Public Opinion Quarterly (publishedVersion)
SSRN Electronic Journal (acceptedVersion)
HighWire Press Open Archive (submittedVersion)
Topics: Social Sciences › Sociology and Political Science › Media Influence and Politics
Social Sciences › Communication › News Media Framing and Political Communication
Social Sciences › General Social Sciences › Computational and Text Analysis Methods
Keywords: media bias, ideological bias, news framing, media coverage of politics, partisan bias, political scandal, news selection

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Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis

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