Brendan Nyhan · Journal of Economic Perspectives, 2020 · ~6–7 min read
False beliefs are a real problem. So is the panic about them.
Nyhan reviews the research on political misperceptions: what they are, why people hold them, where they come from and what reduces them. His verdict: the problem is serious, but the “post-truth” era is not supported by evidence.
Seven terms to know before we start.
- Misperception
- belief in a claim that is false or unsupported by convincing, systematic evidence.
- Misinformation
- the false or unsupported claim that produces a misperception.
- Expressive responding
- giving the survey answer that flatters your side, not the one you believe.
- Illusory truth effect
- repeated claims feel true simply because they feel familiar.
- Directionally motivated reasoning
- wanting a conclusion that fits your side overrides wanting to be accurate.
- Backfire effect
- the largely disproven idea that corrections strengthen false beliefs.
- Demand vs. supply side
- why people believe false claims vs. who produces and spreads them.
Nyhan defines the problem by what people believe, not by what liars intend.
A misperception is a belief in a claim that is false, or unsupported by convincing, systematic evidence. Misinformation is the claim that creates it. Nyhan avoids “lie” and “disinformation” because both require knowing the speaker’s intent, which we rarely can. Counting unsupported claims also captures conspiracy theories that can’t be strictly disproven.
Misperceptions can reshape real policy.
In 2009, Sarah Palin claimed Obama’s health reform would create “death panels” deciding who deserved care. It was false, yet within weeks three in ten Americans believed it. The myth changed the law: a once-bipartisan provision paying doctors to discuss end-of-life care with patients was dropped from the bill to avoid fuelling the controversy.
False beliefs often follow party lines and outlive their corrections.
After the 2016 election, most Trump supporters believed millions of people had voted illegally, while half of Clinton voters believed Russia had altered the vote count. Neither was true. Myths are also durable: after years of debunking, about a third of Americans still believed vaccines cause autism.
Surveys can make misperceptions look more common than they are.
Most evidence comes from surveys, which have blind spots. People answer on the spot, so some “beliefs” are really guesses. Some are partisan cheerleading: shown labelled photos of the 2009 and 2017 inauguration crowds, some Trump supporters insisted his visibly smaller crowd was bigger. A few respondents simply troll. Paying for correct answers narrows partisan gaps, so not every answer is sincere.
Still, most partisan differences in belief are real. People act on them.
Even when people are paid for accuracy, about two-thirds of the partisan gap survives, according to one study. Beliefs also show up in behavior, not just answers. Partisans trust vaccines more when their party holds the White House. During COVID, Republican and Democratic counties differed in how much people moved around, matching their views of the danger.
Fixing a false belief often doesn’t change anyone’s opinion.
Myths and matching policy views go together, but often the belief is just a rationalization of a preference held anyway. When experiments correct the facts, beliefs improve but opinions often stay put: a 2016 fact-check of Trump’s claims about rising crime corrected readers’ beliefs without reducing their support for him. And a myth’s effect on a whole debate can’t be measured: we can’t rerun history without it.
Hearing a claim again and again makes it feel true.
The first vulnerability is simple exposure. A claim we’ve met before is easier to process, and our minds mistake that familiarity for truth, even when we know better. This is the “illusory truth” effect. Exposure is also very uneven: a small group of heavy consumers of partisan and low-quality news sees most of the dubious content, so that’s where misperceptions pile up.
We rarely stop to check, and we trust our own side’s messengers.
Misperceptions also spread when we skip scrutiny. People who go with their gut rather than reasoning things through are worse at telling false headlines from real ones. A simple reminder to think about accuracy reduces sharing of false news. We also use the source as a shortcut: a claim becomes more believable to a leader’s supporters, and less to his opponents, just by being attributed to him.
We believe what suits our side, and knowing more can make it worse.
The strongest force is directionally motivated reasoning: the wish to reach a conclusion that fits our side overwhelms the wish to be accurate. We pick apart unwelcome evidence and wave the welcome kind through. Knowledge doesn’t protect us, because well-informed people are better at spotting which claims suit them. Nyhan notes this is hard to separate from simply having different prior beliefs.
Many myths start at the top. Elites supply them, and followers adopt them.
The most prominent misperceptions often begin with politicians, pundits and partisan media. Climate change shows how. In the 1990s, conservatives were actually more likely than liberals to accept the science; as Republican leaders voiced denial, belief split along party lines. The gap isn’t ignorance, since both parties know similar amounts of science. It comes from following elite cues, and it’s widest among the most politically engaged.
Misinformation is also a business.
Polarization rewards attacking the other side, and new media gives elites cheap, targeted channels. Commercial outlets profit too. Polarized audiences want content that confirms and enrages them, it’s cheap to produce without original reporting, and social media lets a new site reach readers as easily as an established one. These incentives operate across the political spectrum.
Echo chambers are overstated, but falsehood spreads fast to a small, intense audience.
Most people aren’t sealed in filter bubbles: they consume little political news, or a fairly balanced mix. Still, on Twitter false claims spread farther and faster than true ones, probably because they’re novel. But exposure is highly concentrated: before the 2016 election, about 80% of fake-news exposures on Twitter reached just 1% of users.
Truth wins slowly, so fixes matter. They differ by target and timing.
People do update when shown accurate information, and over decades opinion converged on smoking and cancer, or evolution. But updating is slow and incomplete, as with climate change, and sometimes partisans drift further apart. Nyhan sorts interventions by timing (before or after people meet a false claim) and target (the public, political elites or platforms):
| The public | Political elites | Platforms | |
|---|---|---|---|
| Before | Information & media literacy | Reputational incentives | Downranking unreliable sources |
| After | Fact-checks & corrections | Reputational sanctions | Labels & reduced reach |
Correcting the public helps a little, but misses the people who need it, and fades.
Better information in advance faces two problems: there’s no consensus on which institutions to trust, and those most exposed to misinformation rarely seek out reliable sources. Media-literacy tips look promising but untested at scale. Fact-checks do improve accuracy, and the feared “backfire effect” (Nyhan’s own early finding) proved rare, but they reach few of the people who saw the myth, and their effects decay over time.
Targeting the supply looks more promising.
Raising the cost of lying works on politicians: state legislators reminded that fact-checkers were watching were less likely to have their claims publicly challenged. Platforms can act at a scale fact-checkers can’t, downranking repeat offenders and labelling debunked stories. As Facebook stepped up these efforts, the share of Americans visiting untrustworthy websites fell from 27% in 2016 to 7% in 2018.
The “post-truth” panic is itself misinformation.
Some cures threaten free speech, like banning “false” political ads or criminalizing false information, as Kenya did. They feed on a moral panic about a lost golden age of truth. But conspiracy thinking is old, from JFK theories to the “paranoid style” Hofstadter traced to America’s founding, and there’s no evidence misperceptions are worse today. Even warnings about “fake news” backfire, making people distrust real news too. Responses must be proportionate, starting with correcting misinformation about the problem itself.
Discussion, not Nyhan’s argument
- Almost all the evidence comes from the United States.
- Defining away intent leaves out deliberate foreign disinformation campaigns.
- If 1% of users see most fake news, could that 1% still be decisive?
- Written in mid-2020, before January 6 and generative AI.
- He backs platform moderation yet warns against limiting speech. Where’s the line?