Prior exposure increases perceived accuracy of fake news

Fighting misinformation on social media using crowdsourced judgments of news source quality

Many people consume news via social media. It is therefore desirable to reduce social media users’ exposure to low-quality news content. One possible intervention is for social media ranking algorithms to show relatively less content from sources that users deem to be untrustworthy. But are laypeople’s judgments reliable indicators of quality, or are they corrupted by either partisan bias or lack of information? Perhaps surprisingly, we find that laypeople—on average—are quite good at distinguishing between lower- and higher-quality sources. These results indicate that incorporating the trust ratings of laypeople into social media ranking algorithms may prove an effective intervention against misinformation, fake news, and news content with heavy political bias.

Reducing the spread of misinformation, especially on social media, is a major challenge. We investigate one potential approach: having social media platform algorithms preferentially display content from news sources that users rate as trustworthy. To do so, we ask whether crowdsourced trust ratings can effectively differentiate more versus less reliable sources. We ran two preregistered experiments (n = 1,010 from Mechanical Turk and n = 970 from Lucid) where individuals rated familiarity with, and trust in, 60 news sources from three categories: (i) mainstream media outlets, (ii) hyperpartisan websites, and (iii) websites that produce blatantly false content (“fake news”). Despite substantial partisan differences, we find that laypeople across the political spectrum rated mainstream sources as far more trustworthy than either hyperpartisan or fake news sources. Although this difference was larger for Democrats than Republicans—mostly due to distrust of mainstream sources by Republicans—every mainstream source (with one exception) was rated as more trustworthy than every hyperpartisan or fake news source across both studies when equally weighting ratings of Democrats and Republicans. Furthermore, politically balanced layperson ratings were strongly correlated (r = 0.90) with ratings provided by professional fact-checkers. We also found that, particularly among liberals, individuals higher in cognitive reflection were better able to discern between low- and high-quality sources. Finally, we found that excluding ratings from participants who were not familiar with a given news source dramatically reduced the effectiveness of the crowd. Our findings indicate that having algorithms up-rank content from trusted media outlets may be a promising approach for fighting the spread of misinformation on social media.

Fake news on Twitter during the 2016 U.S. presidential election

The spread of fake news on social media became a public concern in the United States after the 2016 presidential election. We examined exposure to and sharing of fake news by registered voters on Twitter and found that engagement with fake news sources was extremely concentrated. Only 1% of individuals accounted for 80% of fake news source exposures, and 0.1% accounted for nearly 80% of fake news sources shared. Individuals most likely to engage with fake news sources were conservative leaning, older, and highly engaged with political news. A cluster of fake news sources shared overlapping audiences on the extreme right, but for people across the political spectrum, most political news exposure still came from mainstream media outlets.

The role of pseudo-cognitive authorities and self-deception in the dissemination of fake news

This paper draws together insights from a variety of fields (including philosophy, psychology, information studies, sociology, politics, and media studies) to synthesize insight into why fake news is created, disseminated, sustained and authorized so as to understand how and why it is successful and how it might be challenged. The premier case for analysis will be Trump, his supporters, his party and his media. Central to this issue is the role of cognitive authorities, a notion first articulated and developed by Patrick Wilson (1983). Honest cognitive authorities have credibility and expertise and are regarded as trustworthy. Their knowledge, based on direct and verifiable knowledge, is sought, communicated and accepted, when an information seeker comes to them about a matter of which an information seeker has come to believe that they have expertise, credibility and knowledge. Pseudo- or false cognitive authorities appear to have the same qualities of credibility, expertise and trustworthiness, but on critical examination they fail in these qualities and strive to impose a partisan agenda irrespective of truth, evidence, logic or facts. Unfortunately, these conditions do not deter believers from accepting them. These authorities are of various types, such news programs or organizations, religious leaders, or social media sites, that create, propagate, authorize and legitimatize fake news stories, that partisan adherents are willing to accept and perpetuate through a form of collective self-deception and who will at the same time denigrate sources and cognitive authorities of genuine and verified information or knowledge. Starting with the InfoWars, we proceed to discuss the nature of the forms of false information on the internet, and the role of deception, particularly self-deception, social self-deception, and collective self-deception in the acceptance real fake news, which is authorized and legitimatized by pseudo-cognitive authorities. In the process we contrast genuine cognitive authorities with dishonest ones, and show how the psychological factors, motivations, and collective self-deception feed each other into a reinforcing collective self-deception so strong it may be equivalent to a cult. This dialogical process (pseudo-cognitive authorities deceiving and self-deceiving themselves and their listeners, who in turn “validate” those authorities through word-of-mouth and seeking and associating with like-minded groups) is reinforced by repetition, the Dunning-Kruger effect, agnotology, and other factors. At the conclusion the roles of information professionals will be examined concerning the difficulties confronting fake news and fake news adherents and developing paths for successful strategies in coping with them.

Less than you think: Prevalence and predictors of fake news dissemination on Facebook

So-called "fake news" has renewed concerns about the prevalence and effects of misinformation in political campaigns. Given the potential for widespread dissemination of this material, we examine the individual-level characteristics associated with sharing false articles during the 2016 U.S. presidential campaign. To do so, we uniquely link an original survey with respondents' sharing activity as recorded in Facebook profile data. First and foremost, we find that sharing this content was a relatively rare activity. Conservatives were more likely to share articles from fake news domains, which in 2016 were largely pro-Trump in orientation, than liberals or moderates. We also find a strong age effect, which persists after controlling for partisanship and ideology: On average, users over 65 shared nearly seven times as many articles from fake news domains as the youngest age group.

Cognitive Reflection and the 2016 U.S. Presidential Election

We present a large exploratory study ( N = 15,001) investigating the relationship between cognitive reflection and political affiliation, ideology, and voting in the 2016 Presidential Election. We find that Trump voters are less reflective than Clinton voters or third-party voters. However, much (although not all) of this difference was driven by Democrats who chose Trump. Among Republicans, conversely, Clinton and Trump voters were similar, whereas third-party voters were more reflective. Furthermore, although Democrats/liberals were somewhat more reflective than Republicans/conservatives overall, political moderates and nonvoters were least reflective, whereas libertarians were most reflective. Thus, beyond the previously theorized correlation between analytic thinking and liberalism, these data suggest three additional consequences of reflectiveness (or lack thereof) for political cognition: (a) facilitating political apathy versus engagement, (b) supporting the adoption of orthodoxy versus heterodoxy, and (c) drawing individuals toward candidates who share their cognitive style and toward policy proposals that are intuitively compelling.

Lazy, not biased: Susceptibility to partisan fake news is better explained by lack of reasoning than by motivated reasoning

Why do people believe blatantly inaccurate news headlines ("fake news")? Do we use our reasoning abilities to convince ourselves that statements that align with our ideology are true, or does reasoning allow us to effectively differentiate fake from real regardless of political ideology? Here we test these competing accounts in two studies (total N = 3446 Mechanical Turk workers) by using the Cognitive Reflection Test (CRT) as a measure of the propensity to engage in analytical reasoning. We find that CRT performance is negatively correlated with the perceived accuracy of fake news, and positively correlated with the ability to discern fake news from real news - even for headlines that align with individuals' political ideology. Moreover, overall discernment was actually better for ideologically aligned headlines than for misaligned headlines. Finally, a headline-level analysis finds that CRT is negatively correlated with perceived accuracy of relatively implausible (primarily fake) headlines, and positively correlated with perceived accuracy of relatively plausible (primarily real) headlines. In contrast, the correlation between CRT and perceived accuracy is unrelated to how closely the headline aligns with the participant's ideology. Thus, we conclude that analytic thinking is used to assess the plausibility of headlines, regardless of whether the stories are consistent or inconsistent with one's political ideology. Our findings therefore suggest that susceptibility to fake news is driven more by lazy thinking than it is by partisan bias per se - a finding that opens potential avenues for fighting fake news.