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

By A. Guess, Jonathan Nagler, Joshua A. Tucker. 2019

1,348 citations recorded by the source corpus.

Fake news sharing in 2016 was rare but significantly more common among older Americans. 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.

Subfields: Artificial Intelligence, Communication, Sociology and Political Science

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Citations in the corpus

Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019, background): “While past studies show that such content is rarely shared, its’ consumption is concentrated within certain groups like older users (Grinberg et al., 2019; Guess et al., 2019).”
Public Health and Online Misinformation: Challenges and Recommendations. (2019, background): “Answering this question feasibly depends on three factors: ( a ) the general quality of health s e .”
The Psychology of Fake News. (2021, background): “Furthermore, our focus is on individual examples ofmisinformation, and not on organized disinformation campaigns (e.g., by the Russian Internet Research Agency, or campaigns relating to global warming or fraud in the 2020 US Presidential Election).”
All the News That’s Fit to Click: The Economics of Clickbait Media (2019, background): “…of my theory, sharing articles is more important than viewing them, and here the results are even more stark (for age, and a bit less stark for ideology): “ Users over 65 shared nearly 7 times as many articles from fake news domains as the youngest age group ” (Guess, Nagler, & Tucker, 2019).”
Effects of COVID-19 Misinformation on Information Seeking, Avoidance, and Processing: A Multicountry Comparative Study (2020, background): “Given that prior research has often focused on the spread of misinformation (Guess et al., 2019; Valenzuela et al., 2019), addressing the implications of that spread on information seeking and processing helps to enrich our understanding of misinformation effects.”
Moderating with the Mob: Evaluating the Efficacy of Real-Time Crowdsourced Fact-Checking (2021, background): “Additionally, while source credibility is used as a proxy for article veracity in a number of studies (e.g., Grinberg et al. 2019; Guess, Nagler, and Tucker 2019; Allen et al. 2020), Allcott and Gentzkow (2017) estimate that only roughly half of the articles from low-credibility domains are indeed…”
Prebunking interventions based on the psychological theory of “inoculation” can reduce susceptibility to misinformation across cultures. (2020, result): “We do, however, find a small consistent decrease with age, which is in line with Guess et al. (2019), who found that older people may be more susceptible to online misinformation.”
Correction Experiences on Social Media During COVID-19 (2021, background): “Interestingly, however, they were also less likely to report being corrected, which is somewhat in contrast to previous research indicating they are also more likely to share misinformation in the first place (Guess et al., 2019).”
Susceptibility to misinformation about COVID-19 around the world (2020, methodology): “The measures used in this study are based on previous research about common predictors of belief in conspiracy theories and misinformation in general [10,16,17,25,36,39,48], as well as specifically about COVID-19 [23,27,39,40,43], as reviewed in the Introduction section.”
Political Psychology in the Digital (mis)Information age: A Model of News Belief and Sharing (2020, background): “Some work has found similar patterns of misinformation belief among both Democrats and Republicans (Path B), while Republicans are more willing to share misinformation (Path C; Guess et al., 2019; Pereira et al., 2020).”
Countering Misinformation and Fake News Through Inoculation and Prebunking (2021, background): “…older people and Conservatives were slightly more susceptible to fake news on the pre-test (which is consistent with other recent work, e.g., Grinberg et al., 2019; Guess et al., 2019, 2020; for a review see Brashier & Schacter, 2020), the inoculation effect was significant across all subgroups.”