Fake News and Bots May Be Worrisome, but Their Political Power Is Overblown

It’s very hard to change people’s minds, especially when so many are already committed partisans.

By Brendan Nyhan  New York Times

How easy is it to change people’s votes in an election?

The answer, a growing number of studies conclude, is that most forms of political persuasion seem to have little effect at all.

This conclusion may sound jarring at a time when people are concerned about the effects of the false news articles that flooded Facebook and other online outlets during the 2016 election. Observers speculated that these so-called fake news articles swung the election to Donald J. Trump. Similarsuggestions of large persuasion effects, supposedly pushing Mr. Trump to victory, have been made about online advertising from the firm Cambridge Analytica and content promoted by Russian bots.

Much more remains to be learned about the effects of these types of online activities, but people should not assume they had huge effects. Previous studies have found, for instance, that the effects of even television advertising (arguably a higher-impact medium) are very small. According to one credible estimate, the net effect of exposure to an additional ad shifts the partisan vote of approximately two people out of 10,000.

In fact, a recent meta-analysis of numerous different forms of campaign persuasion, including in-person canvassing and mail, finds that their average effect in general elections is zero.

Field experiments testing the effects of online ads on political candidates and issues have also found null effects. We shouldn’t be surprised — it’s hard to change people’s minds! Their votes are shaped by fundamental factors like which party they typically support and how they view the state of the economy. “Fake news” and bots are likely to have vastly smaller effects, especially given how polarized our politics have become.

Here’s what you should look for in evaluating claims about vast persuasion effects from dubious online content:

How many people actually saw the questionable material. Many alarming statistics have been produced since the election about how many times “fake news” was shared on Facebook or how many times Russian bots retweeted content on Twitter. These statistics obscure the fact the content being shared may not reach many Americans (most people are not on Twitter and consume relatively little political news) or even many humans (many bot followers may themselves be bots).

Whether the people being exposed are persuadable. Dubious political content online is disproportionately likely to reach heavy news consumers who already have strong opinions. For instance, a study I conducted with Andrew Guess of Princeton and Jason Reifler of the University of Exeter in Britain showed that exposure to fake news websites before the 2016 election was heavily concentrated among the 10 percent of Americans with the most conservative information diets — not exactly swing voters.

The proportion of news people saw that is bogus. The total number of shares or likes that fake news and bots attract can sound enormous until you consider how much information circulates online. Twitter, for instance, reported that Russian bots tweeted 2.1 million times before the election — certainly a worrisome number. But these represented only 1 percent of all election-related tweets and 0.5 percent of views of election-related tweets.

Similarly, my study with Mr. Guess and Mr. Reifler found that the mean number of articles on fake news websites visited by Trump supporters was 13.1, but only 40 percent of his supporters visited such websites, and they represented only about 6 percent of the pages they visited on sites focusing on news topics.

None of these findings indicate fake news and bots aren’t worrisome signs for American democracy. They can mislead and polarize citizens, undermine trust in the media, and distort the content of public debate. But those who want to combat online misinformation should take steps based on evidence and data, not hype or speculation.

Brendan Nyhan is a professor of government at Dartmouth College.

Peer-reviewed publications

Conspiracy and Misperception Belief in the Middle East and North Africa (pre-publication version). Forthcoming, Journal of Politics.

The Role of Information Deficits and Identity Threat in the Prevalence of Misperceptions (pre-publication version). Forthcoming, Journal of Elections, Public Opinion & Parties.

How Conditioning on Posttreatment Variables Can Ruin Your Experiment and What to Do About It (pre-publication version). 2018. American Journal of Political Science 62(3): 760-775.

Fighting the Past: Perceptions of Control, Historical Misperceptions, and Corrective Information in the Israeli-Palestinian Conflict (pre-publication version). 2018. Political Psychology 39(3): 611-631. (with Thomas Zeitzoff)

The Science of Fake News. 2018. Science 359(6380): 1094-1096.

Revisiting White Backlash: Does Race Affect Death Penalty Opinion?(open access). 2018. Research & Politics.

Redefine Statistical Significance (pre-publication version). 2018. Nature Human Behavior 2(1): 6-10. (with 71 co-authors)

Critical Dynamics in Population Vaccinating Behavior (pre-publication version). 2017. Proceedings of the National Academy of Sciences 114(52): 13762-13767.

The Effects of Congressional Staff Networks in the U.S. House of Representatives (pre-publication version). 2017. Journal of Politics 79(3): 745-761.

Differential Registration Bias in Voter File Data: A Sensitivity Analysis Approach (pre-publication version). 2017. American Journal of Political Science 61(3): 744-760

Media Scandals Are Political Events: How contextual factors affect public controversies over alleged misconduct by U.S. governors(pre-publication version). 2017. Political Research Quarterly 70(1): 223-236.

The Nature and Origins of Misperceptions: Understanding False and Unsupported Beliefs about Politics (pre-publication version). 2017. Advances in Political Psychology 38(S1): 127-150.

Classified or Coverup? The Effect of Redactions on Conspiracy Theory Beliefs (pre-publication version). 2016. Journal of Experimental Political Science 3: 109–123.

An Inflated View of the Facts? How Preferences and Predispositions Shape Conspiracy Beliefs about the Deflategate Scandal (open access). 2016. Research & Politics.

Does Public Financing Affect Judicial Behavior? Evidence From the North Carolina Supreme Court (pre-publication version). 2016. American Politics Research 44(4): 587-617.

Understanding Innovations in Journalistic Practice: A Field Experiment Examining Motivations for Fact-Checking (pre-publication version). 2016. Journal of Communication 66(1): 102-138.

Displacing Misinformation about Events: An Experimental Test of Causal Corrections (pre-publication version). 2015. Journal of Experimental Political Science 2(1): 81-93.

The Effect of Fact-checking on Elites: A Field Experiment on U.S. State Legislators (pre-publication version). 2015. American Journal of Political Science 59(3): 628-640.

Connecting the Candidates: Consultant Networks and the Diffusion of Campaign Strategy in American Congressional Elections (pre-publication version). 2015. American Journal of Political Science 59(2): 292-308.

Scandal Potential: How Political Context and News Congestion Affect the President’s Vulnerability to Media Scandal (local copy;pre-publication version). 2015. British Journal of Political Science 45(2): 435-466.

Does Correcting Myths about the Flu Vaccine Work? An Experimental Evaluation of the Effects of Corrective Information(pre-publication version). 2015. Vaccine 33(3): 459-464.

Effective Messages in Vaccine Promotion: A Randomized Trial (pre-publication version). 2014. Pediatrics. Published online March 3, 2014 (doi: 10.1542/peds.2013-2365).

Beliefs Don’t Always Persevere: How Political Figures Are Punished When Positive Information about Them Is Discredited (pre-publication version). 2013. Political Psychology 34(3): 307-326.

The Hazards of Correcting Myths about Health Care Reform. 2013. Medical Care 51(2): 127-132.

The Role of Social Networks in Influenza Vaccine Attitudes and Intentions Among College Students in the Southeastern United States (pre-publication version). 2012. Journal of Adolescent Health 51(3): 302-304.

One Vote Out of Step? The Effects of Salient Roll Call Votes in the 2010 Election (pre-publication version). 2012. American Politics Research 40(5): 844-879.

The Limited Effects of Testimony on Political Persuasion (pre-publication version). 2011. Public Choice 148(3-4): 283-312.

The “Unfriending” Problem: The Consequences of Homophily in Friendship Retention for Causal Estimates of Social Influence (pre-publication version). 2011. Social Networks 33(3): 211-218.

When Corrections Fail: The Persistence of Political Misperceptions(pre-publication version). 2010. Political Behavior 32(2): 303-330.

Bayesian Model Averaging: Theoretical Developments and Practical Applications (pre-publication version). 2010. Political Analysis 18(2): 245-270.

Other publications

All Media Trust Is Local? Findings from the 2018 Poynter Media Trust Survey. The Poynter Institute. 2018.

Social Media, Political Polarization, and Political Disinformation: A Review of the Scientific Literature. Hewlett Foundation. 2018.

Avoiding the Echo Chamber About Echo Chambers: Why Selective Exposure To Like-Minded Political News Is Less Prevalent Than You Think. The Knight Foundation. 2018.

“You’re Fake News!” The 2017 Poynter Media Trust Survey. The Poynter Institute. 2017.

A Checklist Manifesto for Peer Review. 2016. The Political Methodologist 23(1): 4-6.

Increasing the Credibility of Political Science Research: A Proposal for Journal Reforms (pre-publication version). 2015. PS: Political Science & Politics 48(S1): 78-83.

APSA as Amplifier: How to Encourage and Promote Public Voices within Political Science (pre-publication version). 2015. PS: Political Science & Politics 48(S1): 90-93.

Estimating Fact-checking’s Effects: Evidence from a long-term experiment during campaign 2014. 2015. American Press Institute.

The Diffusion of Fact-checking: Understanding the growth of a journalistic innovation. 2015. American Press Institute.

Which Corrections Work? Research Results and Practice Recommendations. 2013. New America Foundation Media Policy Initiative Research Paper.

The Effects of Fact-checking Threat: Results From a Field Experiment in the States. 2013. New America Foundation Media Policy Initiative Research Paper.

Does the US Media Have a Liberal Bias? A Discussion of Tim Groseclose’s Left Turn: How Liberal Media Bias Distorts the American Mind (local copy). 2012. Perspectives on Politics 10(3): 767-771.

Misinformation and Fact-checking: Research Findings from Social Science. 2012. New America Foundation Media Policy Initiative Research Paper.

How Political Science Can Help Journalism (and Still Let Journalists Be Journalists) (local copy). 2011. The Forum 9(1).

Why the “Death Panel” Myth Wouldn’t Die: Misinformation in the Health Care Reform Debate (local copy). 2010. The Forum 8(1).

Party and Constituency in the U.S. Senate, 1933-2004. 2008. InWhy Not Parties?, Nathan W. Monroe, Jason M. Roberts, and David Rohde, eds. University of Chicago Press. (with John Aldrich, Michael Brady, Scott de Marchi, Ian McDonald, David Rohde, and Michael Tofias)

All the President’s Spin: George W. Bush, the Media and the Truth. Touchstone, 2004. (with Ben Fritz and Bryan Keefer)

Current research

Tipping the Scales? Testing for Political Influence on Public Corruption Prosecutions (with Marit Rehavi) [R&R at American Law and Economics Review]

Real Solutions for Fake News? Measuring the Effectiveness of General Warnings and Fact-Check Banners in Reducing Belief in False Stories on Social Media

Taking Corrections Literally But Not Seriously? The Effects of Information on Factual Beliefs and Candidate Favorability

Searching for a Bright Line: The First Year of the Trump Presidencyer review]

Selective Exposure to Misinformation: Evidence from the Consumption of Fake News During the 2016 U.S. Presidential Campaign

Counting the Pinocchios: The Effect of Summary Fact-Checking Data on Perceived Accuracy and Favorability of Politicians

Do People Actually Learn From Fact-Checking? Evidence from a Longitudinal Study During the 2014 Campaign

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