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CueAnon: What QAnon Signals About Congressional Candidates and What it Costs Them

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Abstract

Most research investigates why the public embraces conspiracy theories, but few studies empirically examine how Americans evaluate the politicians who do. We argued that politicians portrayed as supporting QAnon would garner negative mainstream media attention, but this coverage could increase their name recognition and signal positive attributes to voters with low trust in media who would feel warmer toward those candidates. Although we confirm that candidates friendly toward QAnon receive more negative media coverage, our nationally-representative vignette experiment reveals that QAnon support decreases favorability toward candidates, even among seemingly sympathetic sub-populations. A follow-up conjoint experiment, varying whether candidates support QAnon, replicates these findings. This paper is one of the first to highlight the potential costs of elite conspiracy theory support and complicates popular narratives about QAnon.

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Data availability

Data and code needed to replicate the analysis in this manuscript is available on the Political Behaivor Dataverse at https://doi.org/10.7910/DVN/UVVSIR

Notes

  1. We pre-registered our pre-analysis plans at https://osf.io/6e8az/?view_only=5b20d3be656f47d8922d9e38f6c31684. Studies involving human subjects were IRB-approved.

  2. Mainstream media regularly refers to QAnon as a conspiracy theory, but others, such as the Anti-Defamation League refer to it as a movement. Some point out the QAnon is a “super conspiracy theory” that includes many conspiracy theories under its umbrella. At the time of our data collection, QAnon was often covered as a conspiracy theory. We refer to it as such here.

  3. For more on QAnon, see Uscinski (2022).

  4. For example, COVID-19 (birther) conspiracy theories might be more related to trust in science (partisanship).

  5. Matching covariates include candidate gender, previous officeholder, House or Senate race, whether they advanced to the general election, incumbency, and party. We also match on constituency characteristics including open seat, population density, competitiveness, median age, race, proportion attended college, and median household income.

  6. Our corpus does not include TV-first (e.g., Fox, MSNBC, CNN) or blog-style (e.g., Breitbart, Daily Beast) media. Thus, our sample is biased toward mainstream news, which may lean left. Even so, this sample restriction likely underestimates coverage and negative sentiment as we discuss in Online Appendix A.

  7. We pool both waves but analyze each separately in Online Appendix B.

  8. Balance statistics are provided in Table B1.

  9. We preregistered a second moderator variable, party identification. See Online Appendix B.2.

  10. In wave 1, respondents were asked to “Please read the following article about a hypothetical congressional candidate, which might have appeared in a mainstream newspaper.” In wave 2, respondents were asked to “Please read the following article about a congressional candidate, which recently appeared in a mainstream newspaper:” In Tables B2 and B3, the effects are substantively similar when considering waves separately.

  11. In Wave 1 (2), the candidate’s name was John Smith (Cunningham). Pilot tests on Mechanical Turk did not reveal variation in evaluations based on name.

  12. We framed the candidate as losing because (1) our surveys were fielded after elections; we felt describing the candidate as running for Congress would detract from any realism in our study, and (2) we tried to mirror the reality that many QAnon-supporting candidates lost their elections. In Online Appendix B.5, we discuss results of a follow-up study in which we describe the same candidate as having won the election. The results are similar, and there is no evidence to suggest that QAnon-supporting winners are viewed more favorably.

  13. To ensure our articles were perceived as neutral and negative, we conducted a pilot study on Mechanical Turk on September 24, 2020.

  14. We asked: “How warm or cold do you feel toward the candidate in the article? Ratings between 50 degree(s) and 100 degree(s) mean that you feel favorable and warm toward the candidate. Ratings between 0 and 50 degree(s) mean that you don’t feel favorable toward the candidate and that you don’t care too much for him. You would rate him at the 50 degree(s) mark if you don’t feel particularly warm or cold toward the candidate.” We use a feeling thermometer, rather than vote choice, given a concern about ceiling effects among those with low trust in media—who would potentially vote for candidates in either treatment condition, even if intensity of those preferences differed.

  15. To determine within-treatment differences, we conduct 1000 bootstraps and calculate the 0.996 quantile.

  16. In Online Appendix B, we present results of these regressions controlling for seven-point party identification and seven-point ideology (and other covariates). These effects are not driven by the correlation between trust in media, ideology, and party identification.

  17. We balanced on gender to account for a viral TikTok trend that increased female sign ups on Prolific beginning in summer 2021.

  18. We exclude four independents who took our survey.

  19. We chose to present candidates as either supporting or not supporting (rather than actively opposing) for methodological and substantive reasons that we detail in Online Appendix C.

  20. Comparisons between subgroup AMCEs are sensitive to the reference category (Leeper et al., 2020) however, with the exception of prior experience, our attributes are dichotomous. The AMCEs should not be susceptible to baseline effects (Carey et al., 2022). We present the same plots using marginal means in Online Appendix C. Marginal mean plots are exploratory as they were not pre-reigstered.

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Authors and Affiliations

  1. Department of Political Science, University of California, San Diego, 9500 Gilman Drive 0521, La Jolla, CA, 92093, USA

    Benjamin S. Noble

  2. Department of Political Science, Washington University in Saint Louis, One Brookings Drive, St. Louis, MO, 63130, USA

    Taylor N. Carlson

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Correspondence to Benjamin S. Noble.

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Ethical Approval

Taylor Carlson is a member of the Political Behavior Editorial Board. The questionnaires and survey methodology for this study were approved by the Institutional Review Board of Washington University in St. Louis.

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Informed consent was obtained from all individual participants included in the study.

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We thank the Weidenbaum Center on the Economy, Government, and Public Policy for providing support for this project through The American Social Survey (TASS). We thank Nick Anspach, Ted Enamorado, Hans Hassell, Jonathan Green, Christopher Lucas, Jacob Montgomery, Will Nomikos, Mike Olson, Keith Schnakenberg, Betsy Sinclair, and Carly Wayne for helpful feedback on this manuscript. We thank audiences at MPSA 2021 and Florida State University for feedback. We thank Maggie O’Connor, Taylor Degitz, and Oliver Rosand for research assistance. The pre-analysis plan for the experiments is available at: https://osf.io/6e8az/?view_only=5b20d3be656f47d8922d9e38f6c31684.

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Noble, B.S., Carlson, T.N. CueAnon: What QAnon Signals About Congressional Candidates and What it Costs Them. Polit Behav (2024). https://doi.org/10.1007/s11109-024-09957-3

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