Fair and Balanced? Quantifying Media Bias through Crowdsourced Content Analysis

By Ceren Budak, Sharad Goel, Justin M. Rao. 2016

327 citations recorded by the source corpus.

Subfields: General Social Sciences, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/1e1524af594092f41eeae3e18d88371ed2ec6044

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In General Social Sciences

1. E. Peterson
2. Shanto Iyengar
3. Sharad Goel
4. David M. J. Lazer

In Sociology and Political Science

1. Miriam J. Metzger
2. Andrew J. Flanagin
3. Ethan Hartsell
4. David M. J. Lazer
5. Shanto Iyengar
6. E. Peterson
7. B. Swire‐Thompson
8. Sharad Goel

Citations in the corpus

• Cognitive Dissonance or Credibility? A Comparison of Two Theoretical Explanations for Selective Exposure to Partisan News (2020, background): “Budak, Goel, and Rao (2014) provided further evidence supporting CNN as a balanced source.”
• Partisan selective exposure in online news consumption: evidence from the 2016 presidential campaign (2019, methodology): “4 Following a procedure developed by Budak et al. (2016), we recruited coders from Amazon’s Mechanical Turk to classify the content of articles dealing with the presidential election.”
• Fake news on Twitter during the 2016 U.S. presidential election (2019, methodology): “(59) using a mix of crowd-labels and a machine learning model.”
• In Plain Sight: Media Bias Through the Lens of Factual Reporting (2019, background): “According to Budak et al. (2016), FOX is considered strongly right leaning, NYT slightly left leaning, and HPO strongly left leaning.”