Is Seeing Believing? Misinformation & Incidental News Exposure on Social Media

• In Event: Misinformation: Effects

Abstract

Misinformation has significantly aided the rise of illiberal politicians and parties at home and abroad. As seen in the wake of the 2020 U.S. Presidential Election, where claims of fraud encouraged an unprecedented insurrection aimed at overturning the legitimate results, misinformation erodes trust in democratic processes and institutions, creating an informational crisis in which journalism’s traditional role in bolstering the legitimacy of democratic practice has been undermined (Pickard, 2019). Social media platforms, in particular, are rife with misinformation, and these platforms are now regularly implicated as culpable actors in this crisis.

Some research has shown that highly engaged partisans are the most likely to share misinformation and/or believe political falsehoods (Valenzuela et al., 2019; Weeks, 2015). But most people engage with news content on a spectrum of cognitive involvement as they scan their various social feeds (Schäfer, 2020), and it is unclear whether incidental exposure leads to increased likelihood of recall of misinformation or belief in political falsehoods. One possibility is that passive scanners do not engage with news deeply enough to decipher fact and fiction. Alternatively, more detached scrolling may lead to exposure, but not necessarily belief in false stories, because people are not engaged enough to internalize the information. This study examines these possibilities by testing the links between incidental exposure to news on Facebook and three potential effects of misinformation: a) story recall, b) perceived credibility, and c) false belief. Incidental exposure itself arises from a variety of contextual, individual, and technological factors (Weeks & Lane, 2020), including social networks, individual-level habits and motivations, and Facebook’s news algorithm (Thorson et al., 2019). Therefore, this study will test how incidental exposure affects the outcomes above and beyond these factors.

This study relies on a novel design featuring an online rolling cross-sectional survey of adult social media users in the United States (N=1965). Data were collected between September 3 and November 1, 2020. The survey has an incidence rate of 100% and a cooperation rate of 70%. Quotas for age, race, gender, and census region were based on the 2018 American Community Survey. The survey was administered in 17 sampling frames, providing us with a unique opportunity to link survey responses and social media content, because we can locate responses in temporal proximity to actual content known to be circulating on social media. The research team collected external media data from Facebook’s proprietary platform, CrowdTangle. For each sampling frame, we embedded a screenshot of the most popular fake and legitimate news articles in the previous three days (veracity determined by external fact checkers) with source cues photoshopped out of the image.

After exposing respondents to the screenshot, three misinformation outcomes were measured, including story recognition (binary), perceived credibility (three-item scale), and false belief (single-item tailored to the story). The study will test the effects of incidental exposure on these outcomes, in addition to the effects of social media networks (e.g., size, diversity), and individual-level news habits and motivations (purposeful news use, news sharing, intention for using social media, political interest, partisanship, ideology). Finally, the study tests the role of Facebook’s news algorithm, as indicated by whether ‘politics’ and/or ‘news’ were listed in respondents’ interest categories in their Facebook settings. Analysis will be conducted in the multilevel modeling framework (logit for binary outcomes and linear for interval-like outcomes). The sampling frame act as a grouping variable with random slopes and intercepts.

References

Pickard, V. (2019). Democracy without journalism? Confronting the misinformation society. Oxford University Press.

Schäfer, S. (2020). Illusion of knowledge through Facebook news? Effects of snack news in a news feed on perceived knowledge, attitude strength, and willingness for discussions. Computers in Human Behavior, 103, 1-12.

Thorson, K., Cotter, K., Medeiros, M., & Pak, C. (2019). Algorithmic inference, political interest, and exposure to news and politics on Facebook. Information, Communication & Society. Advance online publication.

Valenzuela, S., Halpern, D., Katz, J. E., & Miranda, J. P. (2019). The paradox of participation versus misinformation: Social media, political engagement, and the spread of misinformation. Digital Journalism, 7(6), 802-823.

Weeks, B.E. (2015). Emotions, partisanship, and misperceptions: How anger and anxiety moderate the effect of partisan bias on susceptibility to political misinformation. Journal of Communication, 65(4), 699-719.

Weeks, B. E., & Lane, D. S. (2020). The ecology of incidental exposure to news in digital media environments. Journalism, 21(8), 1119-1135.

Authors

• Matthew Barnidge, University of Alabama

• Trevor H Diehl, University of Vienna

• Daniel Lane, UC Santa Barbara