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This is a pre-analysis plan for the Facebook 2020 Election Research Project like-minded information experiment. The results from the study outlined in this PAP will be published in a paper forthcoming in Nature, July 28, 2023.

Pre-analysis plan for the Facebook 2020 Election Research Project. The results from the study outlined in this PAP will be published in a paper forthcoming in Science, July 28, 2023.

Pre-analysis plans for the Facebook 2020 Election Research Project. The results from the studies outlined in this PAP will be published in two papers forthcoming in Science, July 28, 2023.

Despite the increasing popularity of podcasts as a source of news for many Americans, little is known about their precise role in the information ecosystem. We conduct an online field experiment that examines how consumption of trustworthy news via daily podcasts affects attitudes about politics and the media over a two-week period. Our treatment, deployed at the end of the first of two survey waves, asks subjects to subscribe to a specific high-quality daily news podcast. In addition, treated subjects are asked to turn on mobile push notifications for the podcast. Randomization ensures that we can observe the causal effects of an exogenous change in respondents' news intake, which we measure by short quizzes sent via text message. We hypothesize that our treatment will (1) increase political knowledge, (2) increase overall media trust, (3) reduce affective and issue polarization, and (4) alter news consumption habits after the intervention period, relative to a pure control group. Our results shed light on outcomes linked to the unique possibilities of this medium and, more broadly, on the malleability of mobile-first news consumers' information diets.

In this study, we bring together the often-separate research literatures on media trust and political persuasion to better understand how they interact with each other. To overcome the possibility of confounding in attitudes toward media sources, we create a hypothetical news outlet and manipulate participants’ perceived credibility in this source. We independently manipulate the political slant of this outlet and, in the tradition of research on persuasion, randomly assign subjects to read op-eds on topics attributed to the source’s editorial board (Coppock, Ekins, and Kirby 2018; Guess and Coppock 2018). Our three-wave design allows us to test the persistence of both our credibility manipulation and the persuasive effect of exposure to information from our news source. In doing so, we provide for the first time a comprehensive test of classical expectations that information from trusted intermediaries is more persuasive.

Do personalization algorithms serve up ever more extreme videos to users, resulting in affective and issue polarization? Based in part on vivid anecdotes, a media narrative has taken hold ascribing worrisome power to hidden algorithms. Academic researchers have struggled to add evidence to this debate due to both data limitations and serious research design challenges. We propose a novel experimental approach that seeks to resolve the impasse on this critical question by randomizing the recommendations themselves. Using a custom-built interface that serves sequences of videos from YouTube's API, we create our own variations on the existing recommendation algorithm by manipulating the ideological balance of recommended video content to randomly assigned groups of subjects. This approach enables an attractive combination of experimental control and external validity without the need for reverse-engineering YouTube's blackbox recommendations. Subjects in our study will choose to watch a sequence of short videos and follow recommendations while the interface tracks watch time and other measures of engagement. After the viewing session, participants will be surveyed on issue opinions, affective polarization, and perceptions of media hostility. This pre-analysis plan describes a three-wave study focusing on the issue of gun control.

Do personalization algorithms serve up ever more extreme videos to users, resulting in affective and issue polarization? Based in part on vivid anecdotes, a media narrative has taken hold ascribing worrisome power to hidden algorithms. Academic researchers have struggled to add evidence to this debate due to both data limitations and serious research design challenges. We propose a novel experimental approach that seeks to resolve the impasse on this critical question by randomizing the recommendations themselves. Using a custom-built interface that serves sequences of videos from YouTube's API, we create our own variations on the existing recommendation algorithm by manipulating the ideological balance of recommended video content to randomly assigned groups of subjects. This approach enables an attractive combination of experimental control and external validity without the need for reverse-engineering YouTube's blackbox recommendations. Subjects in our study will choose to watch a sequence of short videos and follow recommendations while the interface tracks watch time and other measures of engagement. After the viewing session, participants will be surveyed on issue opinions, affective polarization, and perceptions of media hostility. This pre-analysis plan describes a three-wave study focusing on the issue of gun control. Amendments on June 17th after sample recruitment but prior to randomization of the treatment.

Understanding the relationship between digital media literacy and susceptibility to dubious sources of onlinecontent is crucial for designing interventions to counter the spread of misinformation (Guess et al. 2020).Unlike some competencies, these skills can potentially be taught, raising the possibility of scalable solutionsto our informational malaise. This project sets out to understand the lasting impact of such initiativesonline. For this project, we test the efficacy of the web extension NewsGuard on shifting online consumptionfrom unreliable sources known for publishing misleading or false content to credible sources. We test if this will also reduce the level of belief in misinformation and increase trust in credible sources.We test if this intervention has larger effects on sub-populations most vulnerable to fake news and if there are downstream effects on other outcomes (affective polarization, political cynicism, etc.) that correlate with viewing, believing, and sharing news from unreliable sources. The following pre-analysis plan was filed before the researchers gained access to the survey or tracking data.

This preregistration documents an experiment embedded in surveys measuring public opinion about COVID-19 and the novel coronavirus in the United States (specifically New Hampshire), United Kingdom (specifically Great Britain), and Canada. Respondents will be randomly assigned to read the percentage of people in their country (i.e., Americans, British, or Canadians) who say that people should get the vaccine once available (p=0.4), the percentage of people in their country that agree that whether to get the vaccine is contentious there (p=0.3), or nothing (p=0.3). We will then measure intention to get a vaccine.

This preregistration documents an experimental intervention implemented in the first and second wave of a two-wave survey measuring public opinion about COVID-19 and the novel coronavirus in Canada. (This study also includes observational survey data that will be analyzed as descriptive/exploratory rather than confirmatory.) Respondents in each wave will be randomly assigned to read four articles adapted from U.S. and U.K. fact-checkers debunking four myths about COVID-19 and the novel coronavirus (independent random assignment; probability .5). Respondents who do not receive the fact-check articles in a given wave are instead shown four placebo articles. (Respondents will only take part in one wave.)

This preregistration documents an experimental intervention implemented in the second and third waves of a three-wave panel survey measuring public opinion about COVID-19 and the novel coronavirus in the United Kingdom (specifically Great Britain). (This study also includes observational survey data and data on web browsing behavior that will be analyzed as descriptive/exploratory rather than confirmatory.) Respondents will be randomly assigned to read four articles adapted from U.S. and U.K. fact-checkers debunking four myths about COVID-19 and the novel coronavirus in wave 2 (independent random assignment; probability .5) and/or wave 3 (independent random assignment; probability .5). As a result, they will be exposed to the fact-check articles in wave 2, wave 3, both waves, or neither wave. Respondents who do not receive the fact-check articles in a given wave are instead shown four placebo articles. This preregistration, which describes the analysis of our experiment, was written with the wave 1 baseline data (which did not include any experimental manipulations) in hand.