🚨Out now in Nature!🚨
A fundamentally new way of fighting misinfo online:

Surveys+field exp w >5k Twitter users show that gently nudging users to think about accuracy increases quality of news shared- bc most users dont share misinfo on purpose

1/ ImageImage
Why do people share misinfo? Are they just confused and can't tell whats true?

Probably not!

When asked about accuracy of news, subjects rated true posts much higher than false. But when asked if theyd *share* online, veracity had little impact-instead was mostly about politics Image
So why this disconnect between accuracy judgments and sharing intentions? Is it that we are in a "post-truth world" and people no longer *care* much about accuracy?

Probably not!

Participants overwhelmingly say that accuracy is very important when deciding what to share Image
We argue the answer is *inattention*: accuracy motives are often overshadowed bc social media focuses attention on other factors, eg desire to attract/please followers

This lines up w past finding that more intuitive Twitter users share lower quality news
We test these competing views by shifting attention towards accuracy in 4 exps (total N=3485) w MTurkers & ~representative sample. If people don’t care much about accuracy, this should have no effect. But if problem is inattention, this should make sharing more discerning.
In one exp, Treatment participants rate accuracy of every news post before indicating how likely they'd be to share it. In Control they just indicate sharing intentions

Treatment reduces sharing of false news by 50%! Most of remaining sharing of false news explained by confusion Image
How about a light-weight prompt?

Treatment=subjects rate accuracy of 1 nonpolitical headline at start of study, subtly priming concept of accuracy

Significantly increases quality of subsequent sharing intentions (reduces sharing of false but not true news) relative to control Image
Next, we test our intervention "in the wild" on Twitter. We build up follower-base of users who retweet Breitbart or Infowars. We then send N=5379 users a DM asking them to judge the accuracy of a nonpolitical headline (w DM date randomly assigned to allow causal inference) Image
We quantify quality of news tweeted using fact-checker trust ratings of 60 news sites (pnas.org/content/116/7/…)- at baseline, our users share links to quite low-quality sites

We assess intervention by comparing links in 24 hrs after receiving DM to links from users not yet DMed Image
We find increase in quality of news retweeted after receiving accuracy-prompt DM! 4.8% increase in avg quality, 9.0% increase in summed quality, 3x increase in discernment. Fraction of RTs to DailyCaller/Breitbart 🡳, to NYTimes 🡱

Sig effect in >80% of 192 model specifications Image
Agent-based simulations show how this positive impact can be amplified by network effects. If I dont RT, my followers dont see it and wont RT, so none of their followers will see it etc. Plus, effect sizes observed in our exp could certainly be increased through optimization Image
We also formalize our inattention account using utility theory. Due to attention constraints, agents can only attend to a subset of terms in their utility fn. So even if you have a strong pref for accuracy, accuracy wont impact sharing choice when attention is directed elsewhere! Image

Fitting model to the experimental data shows avg participant cares about accuracy as much or more than partisanship (confirming survey results)- but attention is often directed away from accuracy

Plus, treatment specifically reduces sharing of more implausible news Image
These studies help us see past the illusion that everyday citizens on the other side must be either stupid or evil- instead, we are often simply distracted from accuracy when online. Another implication of our results is that widely-RTed claims are not necessarily widely BELIEVED
Our treatment could be easily implemented by platforms, eg periodically asking users to rate the accuracy of random posts. This primes accuracy (+generates useful crowd ratings to identify misinformation )

Scalable+doesnt make platforms arbiters of truth!
Here we focused on political news, but in follow-up studies we showed that the results generalize to COVID-19 misinformation as well (eg in this paper that we frantically pulled together in the first few days of the pandemic)
We hope that tech companies will investigate how they can leverage accuracy prompts to improve the quality of the news people share online

To that end, we're really excited about an ongoing collaboration we have with researchers at @Google's @Jigsaw -see psyarxiv.com/sjfbn
We were also really excited to see @tiktok_us, in collaboration with @IrrationalLabs, develop assess and implement an intervention based in part on our accuracy-prompt work

Hoping that @jack @Twitter @Facebook and others will be similarly interested

This study is the latest in our research group's efforts to understand why people believe and share misinformation, and what can be done to combat it. For a full list of our papers, with links to PDFs and tweet threads, see docs.google.com/document/d/1k2…
Finally, if you made it this far into the thread and want to know how this work connects to broader psychological and cognitive science theory, check out this recent review "The Psychology of Fake News" that @GordPennycook and I published in @TrendsCognSci authors.elsevier.com/sd/article/S13…
I'm extremely excited about this project, which took years & was led by @GordPennycook @_ziv_e @MohsenMosleh w invaluable input from coauthors @AaArechar @deaneckles

Please let us know your comments, critiques, suggestions etc. Thanks!!

Ungated PDF: psyarxiv.com/3n9u8
I also wanted to share this @sciam piece that @GordPennycook and I wrote summarizing the paper and related work scientificamerican.com/article/most-p…

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More from @DG_Rand

Aug 21
🚨Out in PoPS🚨
Can crowds help identify misinfo at scale? In this review we show seemingly contradictory findings in the lit are simply due to different analytic approaches. In all data, crowd is highly correlated w experts!
Crowd ratings=useful signals
Professional fact-checking can help reduce misinfo:
➤Warning labels reduce belief & sharing
➤Platforms can downrank flagged content, reducing views

But - the volume of content posted is almost unlimited & exceeds the capacity of professional FCers. How to ID misinfo at SCALE?
Nonexpert users
1) likely view potentially false content first & could respond quickly
2) can flag content overlooked by platforms (eg. non-English)
3) can provide realtime updates on important narratives
But can laypeople effectively identify misinfo?
We review the evidence!
Read 16 tweets
Jun 29
🚨Out in @NatureHumBehav🚨
We examine psychology of misinformation across
16 countries, N=34k
➤Consistent cognitive, social & ideological predictors of misinfo belief
➤Interventions (accuracy prompts, diglit tips, crowdsourcing) all broadly effective

1/ https://t.co/pNagzRcCyHnature.com/articles/s4156…

A lot has been learned about psychology of misinformation/fake news, and what interventions may work. For overview, see @GordPennycook and my TICS review:

BUT almost all of this work has been focused on the west- and misinfo is a GLOBAL problem!
To explore the psych of misinformation through a global lens, our large team (led by
@AaArechar) recruited 34k social media users from 16 countries, matched to national dists on age and gender. They rated 10 true and 10 false COVID headlines, and were randomized to 4 conditions
Read 20 tweets
Dec 19, 2022
🚨Out in @NatureComms🚨
New measure of Twitter users' exposure to misinfo from *ELITES* using @politifact ratings of the elites a user follows
➤Predicts users' misinfo sharing
➤More extreme Reps = more exposure
Check out your own exposure w/ web app! misinfoexpose.com
Here's an (open access) link to the academic paper: nature.com/articles/s4146…
In this thread I'll unpack what we did and what we found
Most misinfo work focuses on laypeople sharing inaccurate news (debunked articles/unreliable domains)
But much misinformation comes from political ELITES - who have big platforms and lots of influence
Field needs to pay more attention to elite misinfo! We made a tool to help
Read 13 tweets
Oct 25, 2022
🚨Accuracy Prompt Meta-Thread🚨
Weve proposed that prompting people to think about accuracy reduces misinfo sharing. But is this effect replicable & robust?
@GordPennycook & I analyzed 20 exps, N=26k
Answer: resounding YES, across many headlines/prompts
Previously we found a disconnect between what people judge as accurate and what they say they'd share- despite not wanting to share things they realize are false. Why? Largely bc people simply forget to consider accuracy when deciding what to share
As a result, prompting people to think about the concept of accuracy in various different ways can increase the quality of the news they share
Read 17 tweets
Apr 14, 2022
🚨New WP🚨
Many people - from Trump to @elonmusk - have accused Twitter of anti-conservative bias

Is this accusation accurate?

We test for evidence of such a bias empirically - and turns out it's more complicated than you might think...

1/ Image
The root of the challenge when inferring political bias is that Republicans/conservatives are substantially more likely to share misinformation/fake news, as shown eg by @andyguess @j_a_tucker @grinbergnir @davidlazer et al science.org/doi/10.1126/sc… science.org/doi/abs/10.112…
and as we show in a large national survey, there is bi-partisan support for platforms taking action to reduce misinformation - this is true both for misinfo in general, and for a specific instance of misinfo (Qanon conspiracy theories) Image
Read 11 tweets
Feb 16, 2022
🚨WP:Examining psychology of misinformation around the globe🚨
Across 16 countries N=34k
➤Strong regularities in cognitive, social & ideological predictors of misinfo belief
➤Broad intervention efficacy (accuracy prompts, literacy tips, crowdsourcing)
1/ ImageImageImage
A lot has been learned about psychology of misinformation/fake news, and what interventions may work - for overview, see @GordPennycook and my TICS review below:

BUT almost all of this work has been focused on the west- and misinfo is a GLOBAL problem!
To explore the psych of misinformation through a global lens, our large team (led by @AaArechar) recruited 34k social media users from 16 countries, matched to national dists on age and gender. They rated 10 true and 10 false COVID headlines, and were randomized to 4 conditions Image
Read 18 tweets

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