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Editorial Bias in Crowd-Sourced Political Information
#MMPMID26331611
Kalla JL
; Aronow PM
PLoS One
2015[]; 10
(9
): e0136327
PMID26331611
show ga
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
inclusion of a citation. We replicate this study on the Wikipedia pages of
deceased as well as recently retired but living senators and find no evidence of
an editorial bias in either. Our results demonstrate that crowd-sourced
information is subject to an editorial bias that favors the politically active.
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