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It’s All in the Name: Source Cue Ambiguity and the Persuasive Appeal of Campaign Ads

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Abstract

As strategies for campaign political advertising become more complex, there remains much to learn about how ad characteristics shape voter reactions to political messages. Drawing from existing literature on source credibility, we expect ad sponsorship will have meaningful effects on voter reactions to political advertisements. We test this by using an original experiment, where we expose a sample of student and non-student participants to equivalent ads and vary only the paid sponsor disclaimer at the end of the message. The only thing that differs across stimuli is whether a political candidate, a known interest group, or an unknown interest group sponsors the advertisement. Following exposure to one of these ads, participants complete a posttest battery of questions measuring the persuasiveness of the message, source credibility, and message legitimacy. We find that ads sponsored by unknown interest groups are more persuasive than those sponsored by candidates or known interest groups, and persuasion is mediated by perceived credibility of the source. We conclude by discussing our findings and their implications for our understanding of contemporary campaigns.

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Notes

  1. Throughout this manuscript, we use the term “independent groups” and “outside groups” interchangeably to reflect both partisan and nonpartisan interest groups not officially associated with a political party or candidate. We also refer to known and unknown interest groups. We use “known groups” to describe more conventional groups very familiar to the public such as the NRA, AARP, and Sierra Club. We use the term “unknown groups” to refer to a host of groups that are not widely known to the general public and whose names such as “American Crossroads,” and “Progress for America,” do not suggest any particular party, ideology, or cause. Though these groups can often be associated with parties, well known partisans, ideologies, issues, unions or corporations, the associations are not immediately obvious to the public and are not widely publicized.

  2. The recent 2010 election cycle sparked discussion of how the emergence of newly formed prominent outside groups such as the conservative “American Crossroads” and the Democratic “Commonsense Ten” would influence the outcomes of prominent races such as that of incumbent Nevada Senator (and Senate Majority Leader) Harry Reid. See http://voices.washingtonpost.com/thefix/morning-fix/american-crossroads-attacks-ha.html and http://undertheinfluence.nationaljournal.com/2010/03/big-time-donors-not-so.php.

  3. Often, simply knowing how a fellow partisan stands on a political issue is sufficient in forming a belief (Tomz and Sniderman 2004). This is especially the case for those individuals with those who have, as Mondak (1993, p. 188) puts it, a “high need for efficiency.” These individuals may simply transfer their approval from one source to another based on a perceived link between the two.

  4. Indeed, source-likeability explains many paradoxes in contemporary politics. For instance, liberals are often perplexed by conservatives’ preference for pro-life policy and the death penalty. Zaller (1992) links these preferences to elite cues, in that voters adopt the positions of trusted, well-known politicians.

  5. Of course, candidates and politicians have many other important goals. However, most assessments of candidate goals and ambitions dating back to Mayhew (1974) agree on the point that the primary goal is reelection given that the other goals can’t be accomplished without attaining or retaining the office.

  6. We did cross the three-condition “source” manipulation with another manipulation—a “high quality” and “low quality” manipulation. The major difference between these two conditions was the presence of absence of music, though we did also vary the tone of the narrator’s voice and several images. The information—the audio voiceover -- was held constant, however. Everyone was exposed to the same information about Dave Reade and John Wilkins. The reason for this manipulation was to see if seemingly amateur, less professional ads—which are common in less well-funded congressional campaigns—are as influential as more professionally, higher quality ads, This manipulation did not have a consistent effect on any of our substantive results, so we collapse across this factor, only exploring the three source manipulations. We generated interactions between “quality” with all the variables in Table 1, finding that quality does not moderate the consequences of source cues on our four dependent variables.

  7. Readers should note that (among others such as the 2007 FEC v. Wisconsin Right to Life decision) the recent U.S. Supreme Court Ruling on Citizens United vs. Federal Election Commission (2010) renders previous restrictions against explicit electioneering by corporate groups unconstitutional. Thus, it is widely expected that we will see more and more ads like this in the future—with non campaign sponsored ads explicitly asking people to vote for or against candidates (Fowler et al. 2010).

  8. Voting for Dave Reade was based on a composite score of (1) would you vote for John Wilkins or Dave Reade? and (2) How confident are you in this decision? The vote choice measure thus varies from 0 to 8.

  9. A model where the experimental covariates are interacted with an indicator of whether the participant is a student or non-student adult indicated that the effects presented in Table 1 do not substantially change across samples.

  10. It is important to note that specifying the NRA prior feelings × NRA Ad interaction does not change the substantive results for the Unknown interest group ad. Since we had no a priori expectations about how feelings towards the NRA moderates the effect of the Unknown interest group or candidate ad, we did not specify an interaction between these variables for the models presented in the text. Nonetheless, if we do specify an NRA Feelings × Unknown interest group ad interaction, it is non-significant for three of the four variables in table 1. There is a marginally significant interaction for legitimacy. This suggests that, on the whole, NRA prior beliefs do not condition how people respond to the other stimuli.

  11. The point estimates were derived and the hypotheses tested from Table 1. Specifically, the point estimates in Fig. 2 are estimates for each dependent variable across levels of the treatment variable, holding the covariates at their respective means and modes. The hypothesis tests are from the regression equation correcting for the effects of the three control covariates—ideology, gender, and race—as well as prior beliefs towards the NRA.

  12. To conduct this analysis, we vary how feeling towards the NRA is scaled, and then regenerate the interactions and re-estimate the models in Table 1. For instance, if evaluations towards the NRA are coded from 0 to 1, where low scores indicate “not favorable,” then in the model with the interaction between the NRA Ad × NRA feelings, the lower order effect of NRA Ad represents the contrast—or difference—between the NRA Ad with the baseline Candidate Ad for individuals who feel not favorable to the NRA. By re-estimating the same equation, but with NRA evaluations coded where 0 denotes positive feelings (i.e., the variable is coded from −1 to 0), now the dummy for the NRA ad denotes the difference between the NRA ad and the Candidate ad at high levels of favorability towards the NRA.

  13. Correlations between latent variable disturbances were also specified. This is common in structural equation modeling, as it simply means that the residuals of the latent constructs may remain even after accounting for the causal relationships. In other words, the model does not explain all of the variation and covariation of latent constructs. No a priori reasons were expected for the errors of the indicators to be related, so we did not model these. All indicator variables were treated as categorical.

  14. Readers unfamiliar with structural equation modeling should note the importance of these estimates. Unlike their observed variable counterparts—such as OLS—SEMs require a good-fit-to data, otherwise, parameter estimates may be biased. In general, a CFI and TLI greater than 0.9 is indicative of a good fit, and an RMSEA and WRMR of less than 0.10 and 0.9, respectively, indicate a good fit.

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Acknowledgments

We thank one of our anonymous reviewers for articulating this.

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Correspondence to Christopher Weber.

Appendix 1: Pretest Question Wording, Summary Statistics, and Correlations

Appendix 1: Pretest Question Wording, Summary Statistics, and Correlations

Pretest

On the next page, we ask that you use a feeling thermometer to indicate your degree of liking or disliking for a variety of people and social groups. Use this thermometer to indicate how warm or cool you feel towards the group. Zero means you feel cool and 100 means you feel warm, and 50 means you feel neutral.

Feelings towards the National Rifle Association (0 [Cold] to 100 [Warm])

*This question was masked in a series of feeling thermometer questions. Participants were also asked about NARAL Pro Choice America, Republicans, Democrats, The U.S. Military, The Supreme Court, The President, Congress.

Posttest

Objective persuasion (M = 0.53, SD = 0.23, Min = 0, Max = 1)

If you were eligible to vote in this election, who would you vote for, John Wilkins or Dave Reade? (John Wilkins, Dave Reade)

How confident are you in this decision? (Very Confident, Somewhat Confident, Not Confident, Not at all Confident)

Based on the ad you saw, do you think you would be likely to support Dave Reade in the future? (Extremely Likely, Somewhat Likely, Somewhat Unlikely, Extremely Unlikely)

Subjective persuasion (M = 0.54, SD = 0.26, Min = 0, Max = 1)

In your view, how persuasive was the advertisement? (Very Persuasive, Somewhat Persuasive, Not Persuasive, Not at all Persuasive)

In your view, how convincing was the advertisement? (Very Convincing, Somewhat Convincing, Not Convincing, Not at all Convincing)

Source credibility (M = 0.38, SD = 0.20, Min = 0, Max = 1)

How do you feel towards the sponsor of the advertisement—the group or person that paid for and/or endorsed the ad? (Very Unfavorable, Somewhat Unfavorable, Middle of the Road, Somewhat Favorable, Very Favorable)

How TRUSTWORTHY is the sponsor of the ad? (Extremely Trustworthy, Somewhat Trustworthy, Somewhat Untrustworthy, Extremely Untrustworthy)

How CREDIBLE is the sponsor of the ad? (Extremely Credible, Somewhat Credible, Not very Credible, Not at all Credible)

How likely is it that you would contribute money to the sponsor of the ad? (Extremely Likely, Somewhat Likely, Somewhat Unlikely, Extremely Unlikely)

Legitimacy (M = 0.48, SD = 0.29, Min = 0, Max = 1)

Some people think that political candidates engage in unfair “character assassinations”; others think that candidates engage in “tough but fair” debates. Do you think the sponsor of the ad you watched was engaging in unfair character attacks or a tough but fair debate? (Tough but fair debate, Neither tough nor fair debate nor unfair character attack, Unfair character attack)

Do you think this ad falls within the bounds of what is appropriate in a political campaign? (The ad is very appropriate, The ad is somewhat appropriate, The ad is somewhat inappropriate, The ad is very inappropriate)

Do you think this political advertisement was fair? (Very fair, Somewhat fair, Not very fair, Not at all fair)

Ideology (M = 0.43, SD = 0.24, Min = 0, Max = 1)

Do you consider yourself a liberal, a conservative, a moderate, or what? (Extremely Liberal, Liberal, Somewhat Liberal, Moderate/Middle of the Road, Somewhat Conservative, Conservative, Extremely Conservative, Other [Please Specify])

Gender (Female: M = 0.67, SD = 0.47, Min = 0, Max = 1)

What is your gender? (Male, Female). Reported statistic is percentage female

Race (Nonwhite: M = 0.14, SD = 0.35, Min = 0, Max = 1)

What is your race? (White/Caucasian, African American, Hispanic, Asian, Native American, Pacific Islander, Other [Please Specify]). Reported statistic is percentage nonwhite (see Table 2).

Table 2 Correlation matrix of dependent variables

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Weber, C., Dunaway, J. & Johnson, T. It’s All in the Name: Source Cue Ambiguity and the Persuasive Appeal of Campaign Ads. Polit Behav 34, 561–584 (2012). https://doi.org/10.1007/s11109-011-9172-y

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