NBER WORKING PAPER SERIES
SOCIAL MEDIA AND FAKE NEWS IN THE 2016 ELECTION
Hunt Allcott
Matthew Gentzkow
Working Paper 23089
http://www.nber.org/papers/w23089
NATIONAL BUREAU OF ECONOMIC RESEARCH
1050 Massachusetts Avenue
Cambridge, MA 02138
January 2017, Revised April 2017
We are grateful to Chuan Yu and Nano Barahona for research assistance, and we thank Stanford
University for financial support. Our survey was determined to be exempt from human subjects
review by the NYU and Stanford Institutional Review Boards. The views expressed herein are
those of the authors and do not necessarily reflect the views of the National Bureau of Economic
Research.
At least one co-author has disclosed a financial relationship of potential relevance for this
research. Further information is available online at http://www.nber.org/papers/w23089.ack
NBER working papers are circulated for discussion and comment purposes. They have not been
peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies
official NBER publications.
© 2017 by Hunt Allcott and Matthew Gentzkow. All rights reserved. Short sections of text, not to
exceed two paragraphs, may be quoted without explicit permission provided that full credit,
including © notice, is given to the source.
Social Media and Fake News in the 2016 Election
Hunt Allcott and Matthew Gentzkow
NBER Working Paper No. 23089
January 2017, Revised April 2017
JEL No. C52,C53,D7,H0,J60
ABSTRACT
Following the 2016 U.S. presidential election, many have expressed concern about the effects of
false stories (“fake news”), circulated largely through social media. We discuss the economics of
fake news and present new data on its consumption prior to the election. Drawing on web
browsing data, archives of fact-checking websites, and results from a new online survey, we find:
(i) social media was an important but not dominant source of election news, with 14 percent of
Americans calling social media their “most important” source; (ii) of the known false news stories
that appeared in the three months before the election, those favoring Trump were shared a total of
30 million times on Facebook, while those favoring Clinton were shared 8 million times; (iii) the
average American adult saw on the order of one or perhaps several fake news stories in the
months around the election, with just over half of those who recalled seeing them believing them;
and (iv) people are much more likely to believe stories that favor their preferred candidate,
especially if they have ideologically segregated social media networks.
Hunt Allcott
Department of Economics
New York University
19 W. 4th Street, 6th Floor
New York, NY 10012
and NBER
hunt.allcott@nyu.edu
Matthew Gentzkow
Department of Economics
Stanford University
579 Serra Mall
Stanford, CA 94305
and NBER
gentzkow@stanford.edu
A online appendix is available at http://www.nber.org/data-appendix/w23089
1 Introduction
American democracy has been repeatedly buffeted by changes in media technology. In the 19th
century, cheap newsprint and improved presses allowed partisan newspapers to expand their reach
dramatically. Many have argued that the effectiveness of the press as a check on power was signif-
icantly compromised as a result (for example, Kaplan 2002). In the 20th century, as radio and then
television became dominant, observers worried that these new platforms would reduce substantive
policy debates to sound bites, privilege charismatic or “telegenic” candidates over those who might
have more ability to lead but are less polished, and concentrate power in the hands of a few large
corporations (Lang and Lang 2002; Bagdikian 1983). In the early 2000s, the growth of online
news prompted a new set of concerns, among them that excess diversity of viewpoints would make
it easier for like-minded citizens to form “echo chambers” or “filter bubbles” where they would
be insulated from contrary perspectives (Sunstein 2001a, b, 2007; Pariser 2011). Most recently,
the focus of concern has shifted to social media. Social media platforms such as Facebook have a
dramatically different structure than previous media technologies. Content can be relayed among
users with no significant third party filtering, fact-checking, or editorial judgment. An individual
user with no track record or reputation can in some cases reach as many readers as Fox News,
CNN, or the New York Times.
Following the 2016 election, a specific concern has been the effect of false stories—“fake
news,” as it has been dubbed—circulated on social media. Recent evidence shows that: 1) 62
percent of US adults get news on social media (Gottfried and Shearer 2016); 2) the most popular
fake news stories were more widely shared on Facebook than the most popular mainstream news
stories (Silverman 2016); 3) many people who see fake news stories report that they believe them
(Silverman and Singer-Vine 2016); and 4) the most discussed fake news stories tended to favor
Donald Trump over Hillary Clinton (Silverman 2016). Putting these facts together, a number of
commentators have suggested that Donald Trump would not have been elected president were it
not for the influence of fake news (for examples, see Parkinson 2016; Read 2016; Dewey 2016).
Our goal in this paper is to offer theoretical and empirical background to frame this debate. We
begin by discussing the economics of fake news. We sketch a model of media markets in which
firms gather and sell signals of a true state of the world to consumers who benefit from inferring
that state. We conceptualize fake news as distorted signals uncorrelated with the truth. Fake news
arises in equilibrium because it is cheaper to provide than precise signals, because consumers
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cannot costlessly infer accuracy, and because consumers may enjoy partisan news. Fake news may
generate utility for some consumers, but it also imposes private and social costs by making it more
difficult for consumers to infer the true state of the world—for example, by making it more difficult
for voters to infer which electoral candidate they prefer.
We then present new data on the consumption of fake news prior to the election. We draw on
web browsing data, a new 1,200-person post-election online survey, and a database of 156 election-
related news stories that were categorized as false by leading fact-checking websites in the three
months before the election.
First, we discuss the importance of social media relative to sources of political news and in-
formation. Referrals from social media accounted for a small share of traffic on mainstream news
sites, but a much larger share for fake news sites. Trust in information accessed through social
media is lower than trust in traditional outlets. In our survey, only 14 percent of American adults
viewed social media as their “most important” source of election news.
Second, we confirm that fake news was both widely shared and heavily tilted in favor of Donald
Trump. Our database contains 115 pro-Trump fake stories that were shared on Facebook a total of
30 million times, and 41 pro-Clinton fake stories shared a total of 7.6 million times.
Third, we provide several benchmarks of the rate at which voters were exposed to fake news.
The upper end of previously reported statistics for the ratio of page visits to shares of stories on
social media would suggest that the 38 million shares of fake news in our database translates into
760 million instances of a user clicking through and reading a fake news story, or about three
stories read per American adult. A list of fake news websites, on which just over half of articles
appear to be false, received 159 million visits during the month of the election, or 0.64 per US
adult. In our post-election survey, about 15 percent of respondents recalled seeing each of 14
major pre-election fake news headlines, but about 14 percent also recalled seeing a set of placebo
fake news headlines—untrue headlines that we invented and that never actually circulated. Using
the difference between fake news headlines and placebo headlines as a measure of true recall and
projecting this to the universe of fake news articles in our database, we estimate that the average
adult saw and remembered 1.14 fake stories. Taken together, these estimates suggest that the
average US adult might have seen perhaps one or several news stories in the months before the
election.
Fourth, we study inference about true versus false news headlines in our survey data. Educa-
tion, age, and total media consumption are strongly associated with more accurate beliefs about
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whether headlines are true or false. Democrats and Republicans are both about 15 percent more
likely to believe ideologically aligned headlines, and this ideologically aligned inference is sub-
stantially stronger for people with ideologically segregated social media networks.
We conclude by discussing the possible impacts of fake news on voting patterns in the 2016
election and potential steps that could be taken to reduce any negative impacts of fake news. Al-
though the term “fake news” has been popularized only recently, this and other related topics have
been extensively covered by academic literatures in economics, psychology, political science, and
computer science. See Flynn, Nyhan, and Reifler (2017) for a recent overview of political mis-
perceptions. In addition to the articles we cite below, there are large literatures on how new infor-
mation affects political beliefs (for example, Berinsky 2017; DiFonzo and Bordia 2007; Taber and
Lodge 2006; Nyhan, Reifler, and Ubel 2013; Nyhan, Reifler, Richey, and Freed 2014), how rumors
propagate (for example, Friggeri, Adamic, Eckles, and Cheng 2014), effects of media exposure
(for example, Bartels 1993, DellaVigna and Kaplan 2007, Enikolopov, Petrova, and Zhuravskaya
2011, Gerber and Green 2000, Gerber, Gimpel, Green, and Shaw 2011, Huber and Arceneaux
2007, Martin and Yurukoglu 2014, and Spenkuch and Toniatti 2016; and for overviews, DellaVi-
gna and Gentzkow 2010, and Napoli 2014), and ideological segregation in news consumption (for
example, Bakshy, Messing, and Adamic 2015; Gentzkow and Shapiro 2011; Flaxman, Goel, and
Rao 2016).
2 Background: The Market for Fake News
2.1 Definition and History
We define “fake news” to be news articles that are intentionally and verifiably false, and could
mislead readers. We focus on fake news articles that have political implications, with special at-
tention to the 2016 US presidential elections. Our definition includes intentionally fabricated news
articles, such as a widely shared article from the now-defunct website denverguardian.com with
the headline, “FBI agent suspected in Hillary email leaks found dead in apparent murder-suicide.”
It also includes many articles that originate on satirical websites but could be misunderstood as
factual, especially when viewed in isolation on Twitter or Facebook feeds. For example, in July
2016, the now-defunct website wtoe5news.com reported that Pope Francis had endorsed Donald
Trump’s presidential candidacy. The WTOE 5 News “About” page disclosed that it is “a fantasy
news website. Most articles on wtoe5news.com are satire or pure fantasy,” but this disclaimer was
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