DIRECT AND INDIRECT HARMS OF MISINFORMATION

Fears about the impacts of misinformation are fueled by the perception of frequent, everyday encounters with misinformation: 89% of Americans report encountering made-up news at least sometimes, and Americans are more likely to identify made-up news as a critical problem than climate change, racism, and illegal immigration (Mitchell et al. Reference Mitchell, Gottfried, Stocking, Walker and Fedeli2019). Notably, 25% of tweets spread during the 2016 U.S. presidential elections were fake or misleading (Bovet and Makse Reference Bovet and Makse2019), and subsequent politically oriented misinformation culminated in a violent insurrection after the 2020 election. These recent events highlight the potential for misinformation to deepen social and political fractures by exacerbating polarization, undermining accountability and rational deliberation, and decreasing trust in institutions and media as part of a vicious cycle.

While the use of misinformation for political ends is as old as politics itself (Arendt Reference Arendt1973; O’Shaughnessy Reference O’Shaughnessy2004), new technological trends are potentially historically transformative. One such development is the emergence of new sophisticated methods to produce digitally altered or fabricated audio, images, or videos, known as “deepfakes,” which result from advances in artificial intelligence techniques such as generative adversarial networks and diffusion models. Deepfakes are produced using approaches such as facial swapping, facial animation, and the creation of entirely synthetic images or audio. Notably, there are less sophisticated techniques referred to as “cheapfakes” or “shallowfakes” which involve basic splicing, editing, or decontextualizing of audio or visual media but still present similar risks (Barari, Lucas, and Munger Reference Barari, Lucas and Munger2021; Tandoc, Lim, and Ling Reference Tandoc, Lim and Ling2018). Furthermore, advanced large language models and multi-modal models popularized in 2022, such as ChatGPT and Copilot, have significantly democratized the ability to create synthetic media. These models can generate realistic text, images, audio, and even video, making it easier for individuals to create synthetic media content that can mimic human-generated content with increasing accuracy. That is, while advanced media creation and manipulation capabilities were previously restricted to professionals through time-consuming and expensive efforts, it is increasingly straightforward for non-sophisticated actors to generate highly convincing fake video, images, audio, and text rapidly and at low cost.

The widespread accessibility of these models, including as a trend on popular social media platforms, has raised concerns about the potential misuse and manipulation of information, further highlighting the need for robust detection, verification, literacy, and governance efforts to combat the spread of misinformation and deception in digital media. Concerns surrounding deepfakes and AI-generated text-based misinformation have now permeated society: 90% of the public say altered video and images cause confusion (Mitchell et al. Reference Mitchell, Gottfried, Stocking, Walker and Fedeli2019), news media and technical experts report severe challenges in establishing the authenticity of content (Toews Reference Toews2020), and politicians have raised alarm and urged legislative activity as well.

Although some experts previously suggested that the impact of deepfakes would be limited, examples of problematic uses are now proliferating in the political arena. For example, deepfakes have been used to discourage supporters of opposing parties from voting in an Indian election, to influence attitudes and military responses to the Russian invasion of Ukraine, and to depict a false bombing of the U.S. Pentagon. Of particular relevance for this study, deepfakes have been used to depict specific politicians engaging in controversial acts or making offensive statements. For example, videos have allegedly exposed sex scandals involving Malaysian deputy minister Shamsul Iskander and Brazilian governor João Doria, though—critically—there has been debate in both cases regarding whether the videos are deepfakes or authentic (Toews Reference Toews2020). Still other politically salient deepfakes have featured U.S. presidents Donald Trump and Barack Obama, French president Emmanuel Macron, Ukrainian president Volodmyr Zelensky, and Russian president Vladimir Putin. This content has even been shared by prominent political figures: Republican Representative Steve Scalise’s office created and shared a cheapfake of U.S. president Joe Biden, Donald Trump Jr. shared a deepfake depicting his father’s appearance on a CNN town hall, and the RNC used AI to generate content for an anti-Biden attack ad featuring hypothetical disaster scenarios. In among the most concerning political cases to date, an allegation that a video depicting Gabon’s president as healthy was a deepfake helped to spur an unsuccessful military coup. Given these many examples, one striking implication is that the mere existence of deepfakes may allow for plausible claims of misinformation and lead to significant social and political harms, even when the authenticity of the content is disputed or disproved.

Notwithstanding increased attention and the seemingly consequential examples above, there is scholarly disagreement over the direct effectiveness of misinformation, conceived primarily in terms of the ability of the information to persuade. Analogous to the minimal effects hypothesis in the context of political campaigns (Kalla and Broockman Reference Kalla and Broockman2018), some scholars have argued that the impact of fake news may be modest. According to this perspective, consumption of misinformation may be limited depending on individuals’ media diets, restricted to those with strong partisan preferences, and moderated by individuals’ ability to adjust for bias in news sources (Little Reference Little2018). Moreover, individual fake news messages may not be especially persuasive on their own in the face of the multitude of informational signals people receive and because fake news consumption is only a small portion of overall news and information diets (Guess, Nyhan, and Reifler Reference Guess, Nyhan and Reifler2020; Watts, Rothschild, and Mobius Reference Watts, Rothschild and Mobius2021). However, while it is possible that the direct persuasive effects of fake news may be less than feared, there is much unknown about the multiple possible direct and indirect impacts of misinformation, especially in the medium to long term (Lazer et al. Reference Lazer, Baum, Benkler, Berinsky, Greenhill, Menczer and Metzger2018).

Indeed, it has long been understood that misinformation can serve a variety of purposes beyond direct persuasion about the truth of particular claims. For example, in the context of authoritarian regimes, misinformation has been used as means to signal the power of regimes or to encourage the performance of loyalty (Huang Reference Huang2015; O’Shaughnessy Reference O’Shaughnessy2004). Misinformation can also promote confusion and skepticism. Deepfakes in particular seem especially likely to drive such indirect harms to the informational environment, as individuals may feel they are no longer able to trust their eyes and ears, engendering broader distrust in all content—whether authentic or falsified (Ternovski, Kalla, and Aronow Reference Ternovski, Kalla and Aronow2022). In this sense, while deepfakes “might not always fool viewers into believing in something false,” they may exacerbate uncertainty and distrust, “further eroding our ability to meaningfully discuss public affairs” and discern truth from fiction (Vaccari and Chadwick Reference Vaccari and Chadwick2020a). Appreciating that these effects may be intentional rather than merely incidental is essential if we are to understand the full implications of misinformation. As such, this article examines indirect effects of misinformation and additionally considers whether new tools to promote misinformation (deepfakes) exacerbate or otherwise alter extant challenges.

A THEORY OF THE LIAR’S DIVIDEND

In light of the importance of indirect effects, this paper is concerned with a form of misinformation that owes its existence (in part) to fake news. That is, the widespread awareness of fake news has opened the door to false claims of fake news, whereby politicians or other public figures can—potentially credibly—claim that real news stories are merely fake news or deepfakes, leading to what Chesney and Citron (Reference Chesney and Citron2019) term the “liar’s dividend.” While this tactic of denial and deflection has been made prominent by U.S. President Donald Trump, calls of “fake news” have now been echoed by politicians in Russia, Brazil, China, Turkey, Libya, Poland, Hungary, Thailand, Somalia, Myanmar, Syria, and Malaysia (Erlanger Reference Erlanger2017). This form of misinformation has been used to target political opponents and to deny critical media coverage, even when objective observers and experts find the reporting to be credible. As a few notable examples amongst many, former Spanish Foreign Minister Alfonso Dastis claimed that images of police violence in Catalonia in 2017 were “fake photos” (Oppenheim Reference Oppenheim2017) and American Mayor Jim Fouts called audio tapes of him making derogatory comments toward women and Black individuals “phony, engineered tapes” (Wang Reference Wang2017), despite expert confirmation.

That the systematic usage of misinformation about misinformation—alleging “fake news” or “deepfakes” in response to real stories—has grown in recent years suggests that public figures find this strategy to be effective or beneficial, against the expectations of a minimal effects hypothesis. In particular, politicians may believe such a strategy can be employed to avoid accountability for political abuses or scandals. We therefore hypothesize that this strategy pays off by safeguarding politicians’ reputations: members of the public are less likely to penalize politicians for scandals when they “cry wolf” over fake news and deepfakes. In particular, we expect this strategy to be more effective than three alternative politician communication strategies: (1) non-response, representing an attempt to ignore a scandal and let it blow over; (2) apologizing, arguably a normatively preferable response; or (3) simply denying a scandal without invoking misinformation.

Liar’s Dividend Hypothesis: In the face of scandal, claims of misinformation (fake news or deepfakes) will increase average support for politicians relative to no response, apologizing, or simply denying a scandal. Footnote ³

We propose that a rebuttal claiming that a story is a deepfake or fake news might improve politician support through two potential pathways, associated with respective strategies that politicians have used. First, the public may find claims of “fake news” to be credible due to uncertainty regarding the truth of signals in what many members of the public may perceive as a distorted media environment—a channel we term informational uncertainty. Footnote ⁴ Here, the payoffs of claims of fake news result from misinformation’s truth-undermining effects, or “the principle that any information could be fake” (Ciancaglini et al. Reference Ciancaglini, Gibson, Sancho, McCarthy, Eira, Amann and Klayn2020). The concern is not that “people will be deceived, but that they will come to regard everything as deception” (Schwartz Reference Schwartz2018), particularly because it is easy to challenge the veracity of evidence in a fractured political environment (Hao Reference Hao2019), and harder to disprove these kinds of claims (Galston Reference Galston2020). If consumers of information believe they have no credible signals about truth or falsity of political claims, the result may be increased uncertainty, as individuals lack sufficient information to establish a basic ground truth or make informed choices (Vaccari and Chadwick Reference Vaccari and Chadwick2020b). Thus, even when individuals are motivated to hold accurate beliefs, informational uncertainty undermines their capacity to do so.

To illustrate how informational uncertainty operates in the case of the liar’s dividend, consider the statement of Spanish Minister Alfonso Dastis, who attempted to discredit photos of violence in Catalonia: “I’m sure you have seen what you have seen, but I have seen fake photos that date back to 2012. So, I think we have got to be patient, and look at the situation” (Oppenheim Reference Oppenheim2017). The uncertainty induced by a statement like this (perhaps intentionally) may leave citizens unclear about how to update their evaluation of the politician or scandal. More generally, after learning of an embarrassing moment or political scandal, a member of the public will be more likely to downgrade their evaluation of the politician. However, if the politician then issues a statement disclaiming the story as a deepfake or fake news, then some members of the public may be more uncertain about what is true, decreasing belief in the scandalous story and increasing average support for the politician. We expect these effects to be concentrated among individuals in the middle of the political spectrum, representing individuals less likely to be strong supporters or opponents of partisan politicians.

The proposed channel of informational uncertainty is perhaps most active when individuals are motivated to hold true beliefs and engage in rational updating of beliefs and subsequent evaluations of politicians. In contrast, we suspect that strong supporters are especially likely to react to appeals to their partisan identity and to engage in motivated rather than purely accuracy-driven reasoning (Taber and Lodge Reference Taber and Lodge2006). In an environment of heightened polarization, and without credible and shared informational signals to support rational processing, individuals may be especially prone to abandoning accuracy motivations in favor of partisan “directional” ones (Druckman Reference Druckman2012; Pennycook et al. Reference Pennycook, Epstein, Mosleh, Arechar, Eckles and Rand2021).

These elements of the political environment are highlighted by the second channel, which we term oppositional rallying. To avoid cognitive dissonance in the face of identity-incongruent information (a damaging news story about a preferred politician or party), core supporters or strong co-partisans may be prone to motivated reasoning (Bullock et al. Reference Bullock, Gerber, Hill and Huber2015). Claims that offer congenial information are useful for co-partisans who observe a scandal and seek information to justify their continued support of the politician. The allegation of a deepfake or fake news can provide just this sort of reason for supporters to rally around the politician, disregarding the negative coverage and preserving their positive evaluations of the politician. Such a response may reflect genuine changes in belief, or instead, expressive responding and partisan cheerleading (Peterson and Iyengar Reference Peterson and Iyengar2021). Further, this channel often explicitly invokes references to political opponents, making use of a “devil shift” (Sabatier, Hunter, and McLaughlin Reference Sabatier, Hunter and McLaughlin1987) whereby politicians signal not only their own innocence, but also the guilt of political opponents and media, encouraging supporters to rally against the opposition.

As an example of this strategy, American Mayor Jim Fouts alleged that his opponents were attempting to “hijack [the annual MLK Day] ceremony by releasing more vile, vitriolic, phony tapes against me” and that such an “effort … is designed to distract from my efforts of inclusion for all” (Wang Reference Wang2017). A politician who employs the strategy of oppositional rallying may thus explicitly signal to supporters because they seek to prime partisan directional motives. We therefore expect this mechanism to be most influential when individuals have strong positive associations with a specific politician (Flynn, Nyhan, and Reifler Reference Flynn, Nyhan and Reifler2017), though strong party identification alone may be sufficient to drive these effects, given increasing affective polarization and a heightened connection between partisanship and identity (West and Iyengar Reference West and Iyengar2020). Thus, we expect effects to be stronger for co-partisans, who are more likely to reward rebuttals claiming misinformation that employ the oppositional rallying strategy with greater support for their preferred politician (Craig and Cossette Reference Craig and Cossette2020).Footnote ⁵ In contrast then, strong out-partisans should be less willing to grant a dividend to politicians with an opposing political orientation, and may even prefer to punish politicians who make such claims.

Given the potential accountability concern that claims of misinformation will reduce individuals’ beliefs in real politician scandals, we examine whether both informational uncertainty and oppositional rallying claims are effective in reducing beliefs about the scandal. Nonetheless, these claims of misinformation could trigger other reactions in voters that could lead to improved support for the politician. For example, through claims of misinformation, politicians might be able to signal their strength, or that they share voters’ skepticism of “mainstream media.”

EXPERIMENTAL DESIGN

To address the hypotheses presented above, we conducted five IRB-approved, online survey experiments based on pre-registered designsFootnote ⁷ with a total of 15,287 respondents.Footnote ⁸ The studies consider how Americans react to politicians’ claims of misinformation in response to scandalous news stories presented via text (in Studies 1–5) or video (in Studies 1 and 4). We randomly assigned participants, irrespective of political party, to a real scandalFootnote ⁹ involving one of four politicians—two Democrat and two Republican—making statements that are arguably insensitive or embarrassing.Footnote ¹⁰

In Studies 1, 2, 4, and 5, after viewing the politician scandal, participants were then also randomly assigned to one of three politician responses: no response (control), a rebuttal claiming misinformation which primes informational uncertainty (IU), or a rebuttal claiming misinformation which primes oppositional rallying (OR).Footnote ¹¹ Thus, in Studies 1, 2, 4, and 5, the control non-response represents a politician strategy of ignoring the scandal in hopes that it will blow over. In Study 3, we instead consider how claims of misinformation invoking informational uncertainty compare to two other politician response strategies: an apology and a simple denial without an allegation of misinformation. We include the simple denial and apology treatments in Study 3 to assess whether the current informational environment makes claims of misinformation even more effective than alternative longstanding politician responses to scandal. Table 1 provides an overview of the five studies.

Table 1. Summary Information about Survey Experiments

For the video, text, and politician rebuttal treatments that we describe next, we aimed to reduce media source cues (e.g., by cropping news banners from videos) to (1) maintain symmetry across treatments and improve internal validity and (2) focus on respondent identification with the politician and party rather than the particular media source. While we recognize that such a strategy removes an element of realism in normal news consumption, we thought this approach best balanced concerns about internal versus external validity. Reassuringly, experimental designs with sparser details, albeit less naturalistic, tend to enable researchers to identify the existence of an effect and do not necessarily imply less generalizability (Brutger et al. Reference Brutger, Kertzer, Renshon, Tingley and Weiss2023). Further, the use of multiple stories and averaging results across politicians helps to ensure that our findings are not limited to a single media source, politician, scandal, or political party.Footnote ¹²

The rebuttals alleging misinformation are inspired by real politician statements and are designed to invoke considerations related to informational uncertainty and oppositional rallying, but are not strictly derived from statements made by the depicted politicians themselves. The informational uncertainty rebuttal draws from comments such as those made by Foreign Minister Dastis and by Syrian President Bashar al-Assad, who in an attempt to discredit an Amnesty International report said: “You can forge anything these days… We are living in a fake news era” (Erlanger Reference Erlanger2017). Along these lines, participants in the informational uncertainty treatment group saw the claim in Figure 1a.

For the oppositional rallying rebuttal, we drew inspiration from statements like that of Mayor Fouts, along with comments by then-president Donald Trump on Twitter in response to growing criticism over his handling of the pandemic: “The Fake News Media and their partner, the Democrat Party, is doing everything within its semi-considerable power (it used to be greater!) to inflame the CoronaVirus situation.” Participants in the oppositional rallying treatment group saw the claim in Figure 1b.

Figure 1. Treatment Wordings for Claims of Misinformation

An important aspect of our study is that it addresses sensitive social and political issues in the context of misinformation, an already fraught topic in that interaction with misinformation can harm participants. As such, we carefully considered ethics in the design and administration of our surveys. Foremost, our study unavoidably involved deception, given our focus on misinformation and the liar’s dividend. Our approach to minimizing deception was to use real videos and stories of politicians, rather than, for example, generating a new deepfake or false story. To enable the comparison of different politician communication strategies in the context of misinformation, the research team did attribute various responses to the politicians (e.g., a rebuttal claiming misinformation or apology) that they did not actually make. Given this deception, we debriefed all participants at the end of the study. Second, to avoid exacerbating participant feelings of distrust and uncertainty, our debrief included links to resources on media literacy and digital literacy, such as information on how to spot false news stories.Footnote ¹³ Third, we wanted to avoid the risk that participation in the study would influence real-world political behavior such as voting. Therefore, we chose to use stories about inactive politicians, that is, individuals who are not currently in office or running for office. Fourth, all participants consented prior to participation and were compensated through our survey vendors. Participants were warned that some of the information was offensive, that some information would be withheld, and that additional information about the goals of the study would be provided at the end.

We measure respondents’ belief in the underlying scandal using two outcome questions (“I believe the story about the politician” and “I think that the story about the politician is true”).Footnote ¹⁴ We then use a set of four outcome measures to assess whether respondents supported the politician (“I would support the politician,” “I would defend the politician against critics,” “I would vote for the politician,” and “I would donate to the politician”). Finally, we assess respondents’ trust in media using two outcome questions (“I trust the media” and “I believe that the media reports the news fairly”). All outcome questions use a bipolar 5-point Likert scale with respondents indicating their agreement from “Strongly disagree” to “Strongly agree.” With the goal of reducing variance and improving content validity, we use multiple questions and create pre-registered indices for each outcome.Footnote ¹⁵

To test our hypotheses, we regress the corresponding outcome measure (e.g., the politician support index) on treatment, along with a set of covariates (partisanship, gender, race/ethnicity, age, education, household income, region, media literacy, and digital literacy) to improve precision.Footnote ¹⁶ Our hypotheses and regression specifications are pre-registered and are available at https://osf.io/qpxr8/.Footnote ¹⁷ For the primary regressions used to test our hypotheses, we report standard two-sided p-values based on robust standard errors.Footnote ¹⁸

The samples for Studies 1–3 and 5 were recruited using the Lucid Theorem platform and are demographically proportionate to the U.S. adult population in terms of gender, race/ethnicity, age, and region. Study 4 uses the Prolific platform and its sample is proportionate to the U.S. adult population on gender, race/ethnicity, and age. See SM Table A1 for information about the composition of our samples. We also find no evidence of covariate imbalance in our samples.Footnote ¹⁹ We include two attention screener questions to allow for the analysis of results stratified by level of attentiveness of respondents, shown in SM Section B.4 (Berinsky et al. Reference Berinsky, Margolis, Sances and Warshaw2019). To avoid selection bias, our main analyses do not exclude inattentive respondents, as recommended by Berinsky, Margolis, and Sances (Reference Berinsky, Margolis and Sances2014). Instead, we report results for the full samples as well as for the attentive subsets. Overall, our findings are consistent, if not stronger, among more attentive participants (also see SM Sections A.2 and A.6).

IS THERE A LIAR’S DIVIDEND?

We conducted Study 1 in February 2021 with 2,503 respondents, and we also conducted an exact replication of Study 1, which we label Study 4, in November 2022 with 4,432 respondents. Figure 2 presents the $ 2\times 3 $ factorial design used in both studies, with variation in both the presentation of the politician scandal (text or videoFootnote ²⁰) and the subsequent politician response (no response, a rebuttal invoking informational uncertainty, or a rebuttal invoking oppositional rallying). In order to ensure consistency across the text and video treatments, we create transcripts of the video clips to produce the text-based treatments. The design of Studies 1 and 4 thus allows for examination of the Liar’s Dividend Hypothesis, as well as the Deepfakes Hypothesis, through exploring differences in responses to politician claims of misinformation after video-based versus text-based scandals.

Figure 2. Experimental Design for Studies 1 and 4

Note: The experimental designs for Studies 2 and 5 are similar, but focus exclusively on text treatments and contain additional exploratory elements explained in more detail below. Study 3 also solely examines text treatments, but compares claims of misinformation using the informational uncertainty strategy to apologies and simple denials.

Figure 3 presents standardized treatment effects for Studies 1 and 4 in order to assess the impact of claims of misinformation on politician support. Overall, the results provide strong support for the Liar’s Dividend Hypothesis, at least for text-based scandals. Figure 3a and 3b show that claims of misinformation invoking informational uncertainty significantly increase politician support by around 0.19 (Study 1) to 0.24 (Study 4) standard deviations after text-based scandals, but fail to increase politician support after scandals caught on video. Claims invoking oppositional rallying also significantly increase politician support by around 0.15 (Study 1) to 0.21 (Study 4) standard deviations after text-based scandals. Results are mixed, however, for oppositional rallying claims after video scandals, with insignificant effects in Study 1 but significant increases in politician support (by 0.14 standard deviations) in Study 4.Footnote ²¹

Figure 3. Liar’s Dividend Results for Studies 1 and 4

Note: Based on the Study 1 (Lucid, Feb. 2021, $ n=\mathrm{2,503} $ ) and Study 4 (Prolific, Nov. 2022, $ n=\mathrm{4,432} $ ) samples. All figures display 95% confidence intervals based on robust standard errors. The reference group is composed of respondents who received a non-response from the politician. Full tables of results with covariates available as SM Tables B6 (Study 1), B7 (Study 1, Attentive), B8 (Study 4), and B9 (Study 4, Attentive).

The magnitudes of these liar’s dividend effects for text-based scandals are meaningful, with effect sizes of 0.1 considered “small” and 0.2 “medium” in the political psychology literature (Funder and Ozer Reference Funder and Ozer2019). For context, the largest treatment effect for a single component outcome measure—for example, “I would support the politician”—corresponds to an unstandardized 0.26 point (Study 1) and 0.29 point (Study 4) increase in support along the 5-point Likert scale, for text-based scandals. Another way of making sense of these effects is to examine the impact of the claims of misinformation on opponents of the politicians. In the text control group in Study 1, around 44% of respondents were opponents, measured as the percentage of respondents who disagreed or strongly disagreed that they would “support the politician.” In contrast, claims of misinformation substantially decreased the percentage of opponents in the text treatment groups to around 32%–34%, a 10–12 percentage point reduction.Footnote ²²

Therefore, we find substantial and significant evidence that both strategies for claiming misinformation—invoking informational uncertainty or oppositional rallying—produce a liar’s dividend after text-based scandals. Notably, effects are even larger for three of the four support measures used to create the index—willingness to support, defend, and vote for the politician—while reticence to donate to the politician attenuates combined support as measured by the index (see SM Figure B7). Moreover, Figure 3 reveals that estimates do not vary dramatically by survey-taker attentiveness and are consistent across Studies 1 and 4.

WHY IS THERE A LIAR’S DIVIDEND?

In Studies 2 and 5, we replicate key elements of Studies 1 and 4 and also probe mechanisms behind the liar’s dividend. Studies 2 and 5 differ from Studies 1 and 4 by focusing on text exclusively (no video treatment), as prior findings showed weaker or non-existent liar’s dividend effects for video-based scandals.

For Study 2, we recruited 2,518 participants in April 2021 via Lucid. Participants were randomly assigned to one of the four text-based politician scandals, followed by: no response from the politician (control) or the informational uncertainty rebuttal.Footnote ²⁴ After seeing one of the two responses to the politician scandal, participants answered the same outcome questions as in Study 1 to preserve the integrity of the replication for the informational uncertainty treatment. We followed this component of Study 2 with a secondary experiment embedded in the same survey to separately assess the oppositional rallying treatment. In particular, Study 2 participants were also assigned to a second politician scandal followed by either the control condition or oppositional rallying rebuttal, and accompanied by the support outcome questions.Footnote ²⁵

The objective for Study 5 was to better understand whether individuals’ beliefs about the scandal were impacted by the claims of misinformation. We recruited 2,838 participants in November 2022 via Lucid. We modified the survey questions for Studies 1 and 4 by including a more specific, clear question about belief in the scandal, described in greater detail below, and by directly asking respondents whether they believed the politician’s claim of misinformation.

In the subsections below, we first present results across studies showing strong, consistent liar’s dividend effects in the case of text-based scandals. Then, we explore the mechanisms associated with the oppositional rallying and informational uncertainty strategies by focusing on heterogeneous effects by co-partisanship with the politician and belief in the scandal, respectively. Finally, we discuss impacts on trust in media.

Liar’s Dividend Effects across Studies

Figure 4 shows results for Studies 1, 2, 4, and 5. Figure 4 also presents “pooled” estimates, combining evidence across studies, that are precision-weighted averages of the treatment effects from each study using fixed effects specifications.Footnote ²⁶

Across study arms with text-based treatments, there is strong support for the Liar’s Dividend Hypothesis. As depicted in Figure 4, in seven out of eight cases across four studies, participants who were exposed to claims of misinformation reported higher average levels of willingness to support the politicians when the claims followed a scandal reported in text format. Figure 4a reveals highly consistent liar’s dividend effects for text scandals, with pooled treatment effect estimates of 0.17 and 0.21 standard deviations for the informational uncertainty and oppositional rallying strategies, respectively, and with consistent, if not stronger, results for the attentive subsets of respondents. Overall, given that these dividends are produced through a single politician rebuttal, the gains in politician support are substantial.

Further, as discussed above, Figure 4b shows a more recent liar’s dividend effect for video scandals in the case of the oppositional rallying strategy in Study 4. However, this effect for video represents only one non-null effect out of four cases across two studies. On balance, there is limited evidence that claims of deepfakes in the face of audio-visual evidence boost politician support.

Figure 4. Liar’s Dividend Results for Studies 1, 2, 4, and 5

Note: Based on the Study 1 (Lucid, Feb. 2021, $ n=1,249 $ Text, $ n=\mathrm{1,254} $ Video), Study 2 (Lucid, May 2021, $ n=\mathrm{2,518} $ Text), Study 4 (Prolific, Nov. 2022, $ n=\mathrm{2,151} $ Text, $ n=\mathrm{2,146} $ Video), and Study 5 (Lucid, Nov. 2022, $ n=\mathrm{2,838} $ Text) samples. The pooled estimates are precision-weighted averages of treatment effects from each study using fixed effects specifications. We show results separately for text and video. Full tables of results with covariates available as SM Tables B10 (Text), B11 (Text, Attentive), B12 (Video), and B13 (Video, Attentive).

Co-Partisanship with the Politician

Moreover, we find that claims of misinformation are broadly effective against text-based scandals, producing support gains from not only co-partisans, but also independents and even out-partisans. In the case of oppositional rallying, we hypothesized that claims of misinformation invoking friends and foes would prime partisan political identity and stir up negative sentiments toward perceived political opponents. As a result, we expected rebuttals invoking oppositional rallying to produce the strongest effects for sympathetic co-partisans of the politician. Alternatively, in the case of informational uncertainty, we expected rebuttals invoking this strategy to produce stronger effects on independents, whose lack of partisan attachments may make them more susceptible to feelings of uncertainty and more willing to change their support.

Yet Figure 5 reveals more extensive effects. Figure 5 displays heterogeneous effects of both theoretical channels of the liar’s dividend compared to control. Effects are disaggregated by the co-partisanship of respondents with the politician in their respective treatment, and are produced by pooling respondents across studies and focusing on text scandals for comparability.Footnote ²⁷

Figure 5. Heterogeneous Effects of Oppositional Rallying and Informational Uncertainty in Response to Text-Based Scandals

Note: Based on pooling the Study 1 (Lucid, Feb. 2021, $ n=\mathrm{1,249} $ Text), Study 2 (Lucid, May 2021, $ n=\mathrm{2,518} $ Text), Study 4 (Prolific, Nov. 2022, $ n=\mathrm{2,151} $ Text), and Study 5 (Lucid, Nov. 2022, $ n=\mathrm{2,838} $ Text) samples. Co-partisans are respondents whose self-reported partisanship matches that of the politician whose scandal they read. Out-partisan respondents are from the opposing political party to treatment politicians. For example, self-identified Strong Democrats, Democrats, and Lean Democrats are identified as co-partisans with the Democrat politicians and out-partisans with the Republican politicians depicted in the treatments. Those who identify as independents are classified as independents regardless of the politician party. This coding is a deviation from our pre-analysis plan, reported in SM Table A3. Full tables of results with covariates available as SM Tables B14 and B15 (Attentive sample). SM Section A.3 presents results separately for each study and also explores robustness to alternative specifications of co-partisanship and partisanship.

In line with our expectations, we find that politician claims of misinformation designed to shift the focus to opponents result in significant support gains amongst co-partisans. That is, oppositional rallying produces sizable effects on the order of 0.28 standard deviations for co-partisans. However, these effects are not statistically different from the effects for independents, and while they are statistically different from the effects for out-partisans ( $ p=0.028 $ ), the difference is insignificant in the attentive subset ( $ p=0.159 $ ). Notably, even the gains for out-partisans are relatively substantial and statistically significant (0.17 standard deviations, $ p<0.001 $ ), suggesting that oppositional rallying has even more widespread appeal than anticipated with no evident backlash effect for out-partisans.

Meanwhile, Figure 5 also suggests that, against expectations, independents are not impacted to a greater extent by informational uncertainty than co-partisans. However, rebuttals invoking informational uncertainty do appear relatively less effective for out-partisans, although this difference is much less pronounced and statistically insignificant in the attentive subset.Footnote ²⁸ The informational uncertainty strategy may operate across the partisan spectrum because an environment of heightened uncertainty and distrust of media leads individuals to perceive politicians as relatively more reliable sources than media organizations (Desai, Pilditch, and Madsen Reference Desai, Pilditch and Madsen2020).

While the effects of claims of misinformation are widespread across partisan groups, baseline levels of support vary substantially. Consequently, claims of misinformation appear to move out-partisans, on average, from the “strongly disagree” to the “disagree” category for politician support. In contrast, claims of misinformation appear to move co-partisans, on average, from a neutral position to support (see SM Figures A4–A6). Critically, we also find consistent effects for both strategies when considering Republican and Democratic respondents separately (see SM Figure A8).

In sum, claims of misinformation against text-based scandals are broadly effective, producing liar’s dividend effects that are not solely concentrated within groups determined by co-partisanship or partisanship. While surprising, these findings are consistent with recent findings showing that “persuasive information” (whether true or not) moves individuals who belong to different groups in the same direction and to a similar extent (Coppock Reference Coppock2022; Fowler and Howell Reference Fowler and Howell2023). Even if our treatments, especially oppositional rallying, contain partisan group cues, recent research also suggests that group cues do not necessarily undermine the effects of persuasive messages (Tappin, Berinsky, and Rand Reference Tappin, Berinsky and Rand2023).

Belief in the Scandal

We also expected claims of misinformation invoking informational uncertainty to influence belief in the underlying scandal about the politician, lowering belief in the scandal and resulting in higher politician support. While Studies 1 and 2 (see SM Section B.12) and Study 4 showed insignificant impacts on belief in the scandal, we employed an alternative and clearer measure in Study 5 to better assess impacts on belief in the scandal. The Study 5 belief measure asks respondents whether they agree with the statement that the “politician really said” the arguably offensive comment in the scandal, using the actual wording from the scandal, thereby reducing ambiguity in our prior measure regarding whether belief refers to belief in the underlying scandal or in the claim of misinformation.Footnote ²⁹ Figure 6 presents the distributions of this new belief measure by treatment group in Study 5, which included only text treatments.

Figure 6. Impacts on Belief in the Scandal

Note: Based on the Study 5 (Lucid, Nov. 2022, $ n=\mathrm{2,838} $ ) sample, which included only text treatments. Belief in the scandal is measured by asking respondents whether they agree with the statement that the “politician really said” the arguably offensive comment in the scandal (using the actual wording from the scandal), and ranges from Strongly disagree (1) to Strongly agree (5). SM Figure B1 presents results for the attentive subset of respondents and shows even stronger effects.

Figure 6 reveals that the politicians’ claims of misinformation did reduce belief in the underlying scandal in Study 5. While 44% of individuals in control believed the scandal (scores of 4 or 5 on the outcome scale), only 36% and 35% of individuals who received the claims of misinformation invoking informational uncertainty and oppositional rallying, respectively, believed that the politicians actually made the scandalous remarks. Figure 6 also shows a higher percentage of individuals responding with uncertainty (score of 3) in the treatment groups. These impacts are statistically significant and relatively substantial, as informational uncertainty reduced belief by 0.15 standard deviations ( $ p=0.001 $ ), and oppositional rallying reduced belief by 0.14 standard deviations ( $ p=0.002 $ ). Moreover, we find that believing the politician’s claim is strongly and negatively correlated with belief in the scandal ( $ r=-0.22 $ , and $ r=-0.40 $ for the attentive subset). That is, individuals in treatment who reported greater belief in the politician’s claim of misinformation were also less likely to believe that the scandal had really occurred.Footnote ³⁰ Finally, we also find that believing the rebuttal is strongly and positively associated with support for the politician ( $ r=0.39 $ , and $ r=0.43 $ for the attentive subset). While this could be driven by reverse correlation, it echoes a finding from Study 2 that individuals who believed the politician rebuttals were also much more likely to report that the rebuttal affected their support for the politician (see SM Table A9). Thus, in Study 5, we find evidence for the theorized pathway for informational uncertainty: (1) that claims invoking informational uncertainty reduce belief in the scandal, (2) that belief in the claim of misinformation is associated with the reduction in belief in the scandal, and (3) that belief in the politician claim of misinformation is also associated with increased politician support. While we expected that change in belief would be associated with the informational uncertainty strategy, evidence from Study 5 also suggests that the oppositional rallying strategy reduced belief in the scandal as well.

While findings from Study 5 offer clear support for the influence of rebuttals invoking misinformation on belief in the scandal, the largely mixed and null results regarding belief in Studies 1–4 urge caution. The mixed results could stem from ambiguity in question wording or could be due to weakly held beliefs in survey-measured attitudes generally (Graham Reference Graham2021). Given our mixed and null results across our original versus our newer and preferred measures of belief, we emphasize that the findings about belief depend on the measure used, and that more research is needed to evaluate this pathway. Furthermore, there are likely additional pathways through which claims of misinformation influence politician support independently of changes in belief in the scandal. For example, claims of misinformation could change individuals’ views of the politicians’ motivation to stay in office, or the politician’s ability and willingness to challenge conventional media. Consequently, changes in views about the politician could then be positively associated with politician support.Footnote ³¹

Trust in Media

Beyond the immediate dividends to politicians, does misinformation about misinformation produce additional, more indirect consequences for society as a whole? To answer this question, we examine whether claims of misinformation invoking informational uncertainty or oppositional rallying impact individuals’ trust in media. Table 2 presents results that address the Trust in Media Hypothesis for Studies 1, 2, 4, and 5. We limit the samples to respondents in the text treatment groups due to the insignificant or weaker support impacts for video described above and to enable comparability across studies, as Studies 2 and 5 include only text treatments. However, SM Section B.11 also reports consistent null results for the impact of treatment on trust in media for video-based scandals.

Table 2. Impacts on Trust in Media

Note: With robust SEs and including covariates. Studies 1 and 4 are limited to the text treatment groups for comparability with Studies 2 and 5, which include only text treatments. In Study 2, we did not ask the trust in media questions for the second experiment assessing the oppositional rallying channel. Full table with covariates available as SM Table B16 and for the attentive subset of respondents as SM Table B22. Results are consistent for the attentive subset. * $ p<0.05 $ , ** $ p<0.01 $ , *** $ p<0.001 $ .

Across studies, we find insignificant impacts on trust in media for both misinformation strategies. These results, while against our expectation, are consistent with recent findings showing that persuasive messages can move attitudes about the target of the message (in our case, the politician), but not other related attitudes (in our case, trust in media) (Coppock Reference Coppock2022, 36). It is possible that individuals’ trust in media is already substantially low—indeed, only 28%, 33%, 23%, and 23% of individuals in control (exposed to a politician scandal, but not to any misinformation claims) in Studies 1, 2, 4, and 5, respectively, indicated that they trust the media.

While the results suggest that individuals’ views about the media may not be affected by a single instance of misinformation about misinformation, future research should explore whether more prolonged or repeated exposure to politicians seeking liar’s dividends can erode general trust in media. We return to trust in media when we compare claims of misinformation to alternative politician response strategies in the next section.

IS ALLEGING MISINFORMATION MORE EFFECTIVE THAN OTHER RESPONSES TO SCANDAL?

Results from Studies 1, 2, 4, and 5 indicate that politicians gain a liar’s dividend when alleging misinformation, in response to text-based scandals, rather than remaining silent after scandal. Yet, remaining silent in the face of scandal and attempting to allow a controversy to blow over is only one among several possible politician messaging strategies. It is possible that any active reply by a politician would proffer benefits compared to a non-response. To address this possibility, Study 3 compares claims of misinformation with two additional politician responses: a simple denial and an apology. These latter strategies have been studied previously as prominent types of politician reactions to transgressions (Gonzales et al. Reference Gonzales, Kovera, Sullivan and Chanley1995) and have been found to mitigate reputational damage (Brenton Reference Brenton2011). Compared to these tried-and-true approaches, Study 3 allows us to assess whether claims of misinformation are effective in boosting support specifically because they invoke an environment saturated with misinformation.

For this study, we recruited 2,996 participants in October 2021 via Lucid. Participants were again randomly assigned to one of the four text-based politician scandals that we used in previous studies, followed, via random assignment, by one of three responses: the informational uncertainty rebuttal from prior studies, a simple denial that does not invoke misinformation, or an apology. We chose to use the informational uncertainty rebuttal (as opposed to oppositional rallying) because it most directly references the indirect harms to the informational environment due to misinformation.

We structured the denial and apology statements to be as similar as possible to the rebuttals claiming misinformation. The denial strategy, shown in Figure 7a, represents a flat-out denial common, for example, to politician sex scandals, such as Bill Clinton’s infamous denial.

The apology statement provides an alternative in which the politician acknowledges the truth of the story and apologizes. This allows us to assess whether members of the public are more receptive to politicians who accept responsibility. The wording for this treatment, shown in Figure 7b, is based on the real reaction by John Murtha to the scandal used in our experiment.

Figure 7. Treatment Wordings for Alternative Politician Responses

Rebuttals Invoking Misinformation Compared to Apologies and Simple Denials

Table 3 presents the results for Study 3 regarding the support gains that accrue to politicians from claiming misinformation or simply denying the scandal, along with impacts on belief in the scandal and trust in media. Unlike the prior studies, the comparison group is not politician non-response. Instead, claims of misinformation invoking informational uncertainty and simple denials are compared to an apology.Footnote ³²

Table 3. Allegations of Misinformation and Simple Denials versus Apologies

Note: With robust SEs and including covariates. The reference group is composed of respondents who received an apology by the politician. Two respondents from the sample are excluded due to missing covariate information. Full table with covariates available as SM Table B17 and for the attentive subset of respondents as SM Table B23. * $ p<0.05 $ , ** $ p<0.01 $ , *** $ p<0.001 $ .

We find some evidence that claims of misinformation invoking informational uncertainty are more effective in generating politician support than alternative politician responses. In particular, claims of misinformation are more effective than apologizing (0.10 standard deviations, $ p=0.012 $ ). In contrast, simple denials do not increase politician support relative to apologies ( $ p=0.252 $ ). While support gains from claims of misinformation are larger in magnitude than support gains due to more simple denials, the difference is not significant at conventional levels (0.06 standard deviations, $ p=0.167 $ ). This finding could imply that a liar’s dividend in today’s informational environment is not meaningfully larger than dividends that would have accrued to liars in the past. Yet another possibility is that even simple denials are more effective in today’s informational ecosystem, a possibility that this study cannot directly address. Additionally, while both apologies and simple denials are common politician responses to scandal, an open question is how rebuttals invoking misinformation compare to still other types of responses or variations of the treatments used here.

Table 3 also reveals that the liar’s dividend benefits to politicians are socially costly: they require deceiving the public, relative to the normatively preferable response of apologizing, creating the conditions for more uncertainty and less accountability. Belief in the scandal declines by a sizable 0.33 standard deviations when the public is misled in this way, likely because the apology response explicitly acknowledges the truth of the scandal. Trust in media also declines by 0.12 standard deviations. Simple denials also reduce belief in the scandal by 0.25 standard deviations and trust in media by 0.09 standard deviations. Compared to simple denials, claims of misinformation are marginally more effective in reducing public belief in a real scandal ( $ -0.08 $ standard deviations, $ p=0.054 $ ) but do not have a significantly different impact on trust in media ( $ p=0.344 $ ). Combined with the insignificant impacts on trust in media compared to politician non-response in Studies 1, 2, 4, and 5, it is possible that apologies raise trust in media relative to claims of misinformation and simple denials, as politicians corroborate media reporting on scandals through apologizing.Footnote ³³

The results raise the concern that politicians can benefit by falsely alleging misinformation rather than taking responsibility for a scandal. This extends recent scholarship finding that politicians benefit more from denying scandals than from conceding and offering to take corrective action (Johnson Reference Johnson2018). Relatedly, while our results indicate that simple denials are not statistically more effective than apologies, denials that employ the extra step of alleging misinformation are indeed more beneficial to politicians than apologies. In combination, these findings caution that political accountability in today’s informational environment is especially difficult. Public figures may be incentivized to cry wolf over misinformation even when doing so undermines the foundation of accountability.