Editorial Bias in Crowd-Sourced Political Information

PloS One
Joshua L Kalla, Peter M Aronow

Abstract

The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by i...Continue Reading

References

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Citations

Mar 22, 2019·Psychological Research·Aileen OeberstSteffen Nestler
Feb 14, 2017··Mark ZachryAmanda Menking

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Software Mentioned

Amazon Mechanical Turk
Mechanical
Wikimedia

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