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INTRODUCTION
Political candidates employ campaign advertising in an attempt to persuade members of the
electorate, and there is mounting evidence that such efforts can be successful in influencing voters'
decisions at the polls (Brader 2005; Franz and Ridout 2007, 2010; Huber and Arceneaux 2007;
Johnston, Hagen, and Jamieson 2004). Not all individuals are equally likely to be persuaded by
political advertising, however, and in this paper we explore the limits of the persuasive power of
campaign advertising by examining the ways in which voters' interpersonal discussion networks
shape their susceptibility to persuasion.
Foundational works in the study of political communication argued that interpersonal
discussions play an important moderating role in the process of mass communications (e.g.,
Berelson, Lazarsfeld, and McPhee 1954; Katz and Lazarsfeld 1955). That is, depending on the
composition of an individual's social environment, interpersonal discussions may serve to either
reinforce messages received through the mass media or promote resistance to mass-mediated efforts
at persuasion.
In spite of these early insights, few studies have explicitly taken into account the combined
influence of interpersonal discussion networks and mass media messages on persuasion in the
context of a political campaign (see Schmitt-Beck 2003 for a notable exception). Instead, most have
endeavored to determine which exerts the greater impact on the vote (Beck et al. 2002; Campus,
Pasquino, and Vaccari 2008; Newton 2006). And even though there is widespread speculation in the
literature as to the likely effects of consonant versus dissonant discussion networks on preference
change among voters (Beck 1991), a direct test of the influence of network composition on elites'
attempts at persuasion has yet to manifest. The present study seeks to rectify this considerable
shortcoming. In doing so we employ detailed measures of campaign advertising in 2008 from the
Wisconsin Advertising Project, coupled with information on the partisan composition of voters'
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discussion networks from the 2008-2009 ANES panel study, to examine the possible moderating
impact of citizens' interpersonal discussions on the persuasive effects of political advertising.
INTERPERSONAL NETWORKS AND CAMPAIGN EFFECTS: BEYOND THE TWO-STEP FLOW
On the heels of the Second World War, concerns over the apparent success of Nazi
propaganda efforts led scholars to examine the impact of the mass media on persuasion. They found
that the mass media played little direct role in changing minds, and instead, its impact was mediated
through opinion leaders embedded within social groups. The so-called "two-step flow" model of
media effects would come to dominate the scholarly conversation surrounding the influence of the
mass media in political campaigns in subsequent years, its reign broken only by research into the
ways in which the media shapes how citizens evaluate political candidates and the issues that are
salient to their decisions at the polls.
More recent work on the mass media has argued that, in addition to its indirect persuasive
impact, the media can actually have multiple effects on information processing during the campaign
(e.g., Iyengar and Kinder 1987; McCombs and Shaw 1972). The media can set the political agenda,
frame the debate over the course of the campaign, and prime voters to evaluate candidates in light
of certain traits or issues. It was not long, however, before scholars began to note that the impact of
the media in these arenas was conditioned by interpersonal discussions as well. Interpersonal
discussion networks have been shown to affect the criteria by which candidates are evaluated (Cho
2005; Mendelsohn 1996), limit elites' ability to frame political discourse in their preferred way
(Druckman and Nelson 2003), and curb the media's agenda-setting function (Atwater, Salwen, and
Anderson 1985; Erbring, Goldenberg, and Miller 1980; Wanta and Wu 1992).
At the same time, better data and tighter research designs were beginning to afford scholars
opportunities to reassess the direct effect of mass mediated messages on preference change in the
electorate. Today it is all but settled that the mass media, and in particular televised political
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advertising, has the power to persuade voters to change their minds about which candidate they
support. A number of studies, both experimental and observational in nature, have found that
exposure to TV ads can induce shifts in voters' stated preferences (Brader 2006; Franz and Ridout
2007, 2010; Huber and Arceneaux 2007; Johnston, Hagen, and Jamieson 2004). The effect of
political advertising is hardly absolute, however, as certain individual-level characteristics have been
shown to be key moderators of the effects of televised political ads. Huber and Arceneaux (2007)
find, for instance, that consistent with Zaller's (1992) Receive-Accept-Sample (RAS) model of
opinion change, individuals with middling levels of political awareness are the most likely to be
persuaded by campaign ads.
While certain traits undoubtedly make individuals more or less susceptible to advertising
effects, it is important to remember that voters do not encounter political messages from the mass
media in a vacuum (see Cho et al. 2009). Rather, most individuals are embedded within any number
of often overlapping, social networks (e.g., Huckfeldt and Sprague 1995). These interpersonal
discussion networks serve as conduits through which information gleaned from the mass media can
be relayed (Cho et al. 2009; Katz and Lazarsfeld 1955; Mendelsohn 1996). Televised political ads, in
particular, are likely to become a topic of conversation around the water cooler (McClurg 2004), and
there is ample evidence to suggest that exposure to campaign advertising helps to stimulate political
discussion (Cho 2008, 2011, 2013; Cho et al. 2009; Pan et al. 2006; see also Mondak 1995). Such
findings are entirely consistent with the "two-step flow" model of communication and what Katz
and Lazarsfeld termed the "relay function of interpersonal relations" (1955, 45 emphasis in original).
But Katz and Lazarsfeld also postulated that "person-to-person influences may coincide with
mass media messages and thus either counteract or reinforce their message" (1955, 45; see also Beck
1991; Berelson, Lazarsfeld, and McPhee 1954; Nimmo 1970). They termed this the reinforcement
function of interpersonal communication. It is this secondary characteristic with which we are
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concerned in this paper, as we wish to examine the conditions under which political talk may
moderate the persuasive effects of campaign advertising. In doing so, our investigation aims to test
the hypothesis that interpersonal communication can either enhance or induce resistance to elites'
efforts at persuasion through the mass media. Referred to as the "filter hypothesis" by Schmitt-Beck
(2003), the degree to which discussion networks insulate individuals against attempts at persuasion
or magnify the persuasive effects of campaign appeals depends on 1) the composition of an
individual's discussion network and 2) the relative balance of mass media messages from the
campaigns.
Earlier scholarship, however, has only evaluated evidence in favor of the reinforcement
function of interpersonal communication using measures of exposure to the news media. The
problem with such an approach is that, as Cho notes, "television news, unlike political ads, is not a
persuasive form of communication [and] does not generally favor a certain candidate or party"
(2005, 308). Scholars looking at television news and other news outlets (e.g., news magazines and
newspapers) to speak to the moderating impact of interpersonal discussions on the persuasive power
of the mass media have been forced to make assumptions about which candidates or parties are
supported by particular media outlets (Campus, Pasquino, and Vaccari 2008; Mendelsohn 1996;
Schmitt-Beck 2003; though see de Vreese and Boomgaarden 2006). By contrast, it is much less
difficult to discern who the favored candidate is in a televised political ad.
Moreover, many previous studies of how interpersonal networks can moderate the effects of
the mass media have, by necessity, assumed that political talk takes place within a consonant social
environment. That is, owing to data limitations, and in particular, the paucity of appropriate network
measures, scholars have generally been required to conceptualize any political talk as having the
effect of reinforcing individuals' existing preferences (Cho 2005; Mendelsohn 1996; de Vreese and
Boomgaarden 2006). Studies of social influence, however, point to a surprising amount of
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disagreement within discussion networks (e.g., Huckfeldt, Johnson, and Sprague 2004; Huckfeldt
and Sprague 1995). Co-workers and other discussants outside of individuals' primary groups are
especially apt to provide a counterpoint to their own tightly-held beliefs and political preferences
(Beck 1991; Granovetter 1973; Mutz and Mondak 2005). As such, "the role of political discussion
cannot be understood precisely without considering whether the interactants are homogenous or
heterogeneous" (Cho 2005, 300). In this next section we lay out a series of hypotheses outlining our
expectations regarding the likely impact of different arrangements of individuals' discussion
networks on the persuasive effects of televised political advertising. We root our discussion in the
reinforcement function of the mass media (Beck 1991; Berelson, Lazarsfeld, and McPhee 1954; Katz
and Lazarsfeld 1955; Schmitt-Beck 2003).
EXPECTATIONS
Political awareness has been found to moderate the impact of political advertising on vote
choice. As Katz and Lazarsfeld (1955) noted more than a half-century ago, though, both individual
characteristics and networks of interpersonal communication serve to temper the effects of the mass
media. Individuals in consonant social networks receiving campaign messages that are consistent
with their preferences are likely to strengthen their initial decision to support a particular party or
candidate. We would expect few who are nestled within such a supportive information environment
to change their preferences over the course of the campaign. Homogeneous networks also may aid
individuals in resisting elites' efforts at persuasion through the mass media, serving as "protective
cocoons for an individual's political preferences" (Beck 1991: 378; see also Finifter 1974).
Specifically with respect to the impact of campaign advertising, Patterson and McClure (1976) note
that social groups increase individuals' ability to withstand attempts at manipulation through TV ads.
Here, as throughout this paper, we define persuasion as a shift away from the candidate that a
respondent initially preferred toward the other candidate competing in the general election contest.
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At the opposite extreme, individuals whose own preferences are at odds both with the
balance of the messages they receive from the mass media and with those in their surrounding social
network number among perhaps the most susceptible to efforts at persuasion. Although rare in
comparison to homogenous networks of interpersonal discussion (see Beck 1991), such
arrangements do occur, and offer clear opportunities for political ads to influence voters' decisions.
As Huckfeldt and colleagues write, "Rather than insulating individuals from the external political
environment, social communication carries with it the potential to magnify the consequences of the
external environment by exposing individuals to non-redundant, politically disparate information"
(2004, 215). Berelson, Lazarsfeld, and McPhee (1954: 98-101) likewise identify social environments
that are divided internally as a key condition for preference change.
There is, however, yet another alternative: citizen deliberation--that is, cross-cutting political
discussion within networks--may aid efforts at resisting manipulation through the mass media.
Druckman and Nelson (2003) found that deliberation limited elites' attempts at framing events in
their preferred light. The same is perhaps even more likely to hold true for the persuasive effects of
televised political advertising. The opportunity to discuss the candidates and issues of the day, even
if in the company of those with whom one disagrees, is almost certain to moderate the direct effects
of the candidates' campaign communications.
What of those who are without discussion partners or do not discuss politics with anyone in
their social network? Much as is the case with heterogeneous social networks, we expect such
situations to provide an "open flank" through which the mass media can influence an individual's
preferences (Schmitt-Beck 2003). However, in the absence of opportunities to reinforce the
messages relayed through the mass media that are associated with consonant social environments,
the persuasive effect of political advertising is likely to be lesser than it otherwise might be. We
therefore expect those who do not discuss politics with anyone else to be more influenced by
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messages that run counter to their initial preferences than are those who surround themselves with
like-minded associates. By the same token, they are perhaps less likely to be persuaded to support a
different candidate than would be someone nestled within a social environment that is wholly at
odds with their own political leanings.
We discuss how we intend to explore the relationship between campaign advertising and
disagreement within discussion networks in the following section, and detail the data and measures
that we employ in doing so.
DATA AND METHODS
In order to test our expectations regarding the ways in which network composition serves to
moderate the persuasive effect of political advertising and is, in turn, shaped by exposure to televised
campaign ads, we turn to two data sources: the 2008 Wisconsin Advertising Project and the 2008-
2009 ANES panel study. We use waves nine and ten from the ANES panel study, which were
collected in September and October of 2008 respectively.1 Although we would have liked to utilize
additional waves of the study, the social network battery was only collected in the September wave.
We believe that using information about network composition to predict behavior months before or
after our network measures were administered would force us to make the tenuous assumption that
social networks exhibit little or no change over time (see Djupe, Sokhey, and Neiheisel no date).
Following Klofstad et. al (2013), we created two measures of network disagreement. The
first captures partisan disagreement within an individual's social network, while the second gauges
what scholars have termed "general disagreement." These measures are empirically and conceptually
distinct. According to Klofstad and colleagues (2013), "individuals who perceive general
disagreement have weaker political preferences, while individuals who experience disagreement
1 Individuals in the ANES panel study were interviewed on a rolling basis. Among the individuals in our study, wave nine interviews took place between September 3 and October 2, 2008; wave ten interviews took place between October 3, 2008 and November 5, 2008.
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measured by a lack of shared partisan preferences have stronger political preferences" (Klofstad et
al. 2013: 128). Owing to the fact that they have weaker political preferences, those who perceive
general disagreement are also perhaps more likely than those who report encountering partisan
disagreement to be influenced by mass mediated messages (Zaller 1992). Additionally, while
disagreements may indeed crop up within discussions among persons from different political parties,
partisan differences may not necessarily manifest in cross-cutting political debate (see Gerber et al.
2012). Partisan disagreement is neither a necessary nor sufficient condition for deliberation to occur.
Measures of "general disagreement," however, capture disagreements that are intense enough to be
memorable. It therefore seems likely that general disagreement may moderate the persuasive power
of televised political advertising, while partisan disagreement is unlikely to exert much influence.
In determining the amount of general disagreement present in a discussion network,
respondents were asked the following question about each of their discussion partners: "In general,
how different are [DISCUSSANT NAME]'s opinions about government and elections from your
own views?" Our measure of general disagreement was created by summing the disagreement scales
for each member of the respondent's discussion network and dividing by the total number of
discussants. The latter step was taken to make the scale comparable across respondents with
different numbers of discussion partners.
To create our measure of partisan disagreement we took the mean partisanship score within
each respondent's network and subtracted the respondent's own partisan identity. Respondents were
asked about the party identification of each person within their social network, labeling each not
only as Republican or Democrat, but also as a strong or weak partisan. It is therefore possible to
create a measure of each discussant's party ID that mimics the seven point party identification scale
on which the respondent was placed. As both larger positive and negative numbers on this scale
represent greater degrees of network disagreement, we took the absolute value of the distance
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between the respondent's partisanship score and the average partisanship within her social
environment (see Klofstad et al 2013 for a more detailed treatment of these measures).
[Insert Table 1 about here]
To explore the ways in which network disagreement serves to moderate the persuasive
power of campaign ads we created measures of the number (in thousands of airings) of both
consonant and dissonant political ads to which each respondent could have been exposed.2 Variance in
the number of ads aired by each of the campaigns across media markets and over time makes it
possible to construct individualized measures of potential ad exposure. Temporal variation in ad
volume stems from the fact that the ANES interviewed respondents within each wave over the
period of about a month, while spatial variation can be tied to the ad-buying strategies that are
employed by the presidential campaigns (Shaw 2006). We also control for how often respondents
reported watching TV news--the most popular type of program during which the campaigns
purchase air time (Franz et al 2008).
We operationalize potential exposure to consonant political ads as the number of ads aired
by the presidential candidate the respondent supported in the September wave that were broadcast
between wave nine and wave ten. Potential exposure to dissonant political advertising is
operationalized in much the same way: ads aired between waves nine and ten by the candidate the
respondent did not support in the September wave are counted as carrying a dissonant message (see
Table 1 for descriptive statistics on both ads-based measures).3 In addition to these two ads-based
2 Unfortunately, the 2008-2009 ANES panel study did not include the kind of media use questions necessary to create the standard "shows-based" measure of exposure to political ads that is often employed in studies of campaign advertising (see Freedman and Goldstein 1999). 3 Measures of advertising (both consonant and dissonant) are individualized. Because the ANES provides exact interview dates and the WiscAds data provide exact airings of television ads, we were able to take the variablity of interview dates into account in our measurement of consonant and dissonant ads. Essentially, for each individual in the dataset, we calculated the number of McCain (and Obama) ads that aired prior to the wave nine interview date. We then calculated the number of McCain (and Obama) ads that aired prior to the wave ten interview date. Then, we subtracted the wave nine ad totals from the wave ten ad totals to obtain an individualized measure of the number of McCain (and Obama) ads the respondent was exposed to between the dates of his/her interview.
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measures, our main model also includes a series of product terms geared toward testing whether
network composition conditions the effect of televised campaign advertising on preference change
during the campaign. The variables tapping possible exposure to either consonant or dissonant
political ads were interacted with both measures of network disagreement (general and partisan), as
well as with an indicator for whether the respondent did not discuss politics with anyone during the
campaign.
The dependent variable we employ in testing the moderating impact of network composition
on the persuasive effect of advertising also requires some explanation. It aims to capture preference
change between wave nine and wave ten in the ANES panel study, and ranges from negative one to
one. Respondents received a zero if they were just as certain that they would support a particular
candidate for president in wave ten as they were in wave nine. If, however, a respondent grew more
certain about her initial choice for president, she received a score of one. A score of negative one
was assigned, however, if the respondent moved away from the candidate she supported in wave
nine toward the opposing candidate in the following wave. For instance, if an individual was "slightly
sure" that she was going to vote for Barack Obama as of September, but was undecided about
whom to support when asked the same question in October, she received a score of negative one.
At the same time, someone who was "moderately sure" she would vote for John McCain when
queried about her preference in September but said she was "extremely sure" she would cast her
ballot for the Republican nominee in October would receive a score of one. The modal value this
variable takes is zero, as comparatively few respondents changed their preferences between the two
waves of the survey. Table 1 offers a descriptive look at this key variable.
A number of other variables are used primarily as controls, and require little additional
explanation. The basic model specification we use throughout this study is inspired by Huber and
Arceneaux (2007), and includes controls for gender, age, age squared, race, employment status,
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income, and education. Beyond these demographics we also include variables tapping changes in
partisan identification between waves, strength of partisanship, ideology, political interest, TV news
watching, and an indicator for whether the survey was administered on the day of a major campaign
event (such as one of the debates).
RESULTS
To examine whether individuals' social environments moderate the persuasive impact of
televised political advertising, we estimate a ordered logistic regression model predicting changes in
candidate preferences between wave nine and wave ten on the 2008-2009 ANES panel study.
Results from this model are displayed in Table 2.4 A complete test of our hypotheses dictated that
the model specification include both measures of network disagreement, exposure to consonant and
dissonant campaign ads, a dummy for whether the respondent reported having no discussion
partners, and a series of interaction terms that form the focal point for our investigation. Neither
measure of disagreement achieves statistical significance as a main effect. Conversely, advertising
exposure is statistically significant and behaves as we expect with consonant ads increasing the
likelihood of strengthening one's candidate preferences, while dissonant ads push respondents in the
other direction, inducing change toward the opposing candidate between the two waves of the
survey. Having no discussants has no discernible impact on preference change.
[Insert Table 2 here]
Several of the interaction terms are statistically significant, as both ad measures appear to be
moderated by general disagreement and our indicator for whether the respondent reported having
no discussion partners. As the interpretation of the impact of interaction terms in ordered logit
4 In addition to controlling for the variables mentioned above, we also examined whether living in a closely-contested state had any influence on our results. Controlling for whether the respondent resided in a "battleground" state (one of the seven states in which the presidential election was the closest in 2008--Florida, Indiana, Missouri, Montana, North Carolina, North Dakota, and Ohio) does not change our results. Neither is the battleground indicator statistically significant.
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models is not as straightforward as it is in the linear case (Kam and Franzese 2007), we calculate the
marginal effect of exposure to both consonant and dissonant political ads, examining the impact of a
one standard deviation increase in advertising exposure on preference change, given a certain level
of (general) disagreement within a network.
[Insert Figures 1a and 1b about here]
Starting with the impact of exposure to advertising that is consonant with the respondent's
stated candidate preference in wave nine of the survey, we observe in Figure 1a that a one standard
deviation increase in exposure to consonant political advertising decreases the predicted probability
of persuasion (conceptualized here as movement toward the candidate that the respondent did not
support in wave nine of the study).5 This effect is muted, however, by the structure of individuals'
interpersonal discussion networks, as more general disagreement within a social network decreases
the ability of consonant campaign ads to reinforce respondents' initial candidate choice. The trend
displayed in Figure 1a is only suggestive, as the confidence intervals overlap throughout the range in
which the overall effect is statistically significant. That is, we are unable to say that a one-unit
increase in the amount of general disagreement within a network (moving from "no disagreement"
to "some disagreement") leads to a diminished ability to resist persuasion. The overall trend,
however, suggests that social networks moderate the impact of mass-mediated messages in a way
that is consistent with the results of previous studies and with our own stated expectations.
We find the opposite relationship on display with respect to the effect of consonant
campaign ads on the strength of individuals' preferences, as those residing within networks that are
wholly without disagreement strengthened their resolve to support their chosen candidate after
receiving such messages. Greater levels of disagreement among discussion partners, however, are
associated with decreases in the marginal effect of consonant political advertising until the point
5 Estimates of the marginal effect of campaign advertising, along with simulated 95 percent confidence intervals, were calculated using CLARIFY (Tomz, Wittenberg, and King 2003).
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where, at extreme levels of disagreement (values of three or above on the general disagreement
scale), increases in ad volume have no effect, neither increasing nor decreasing voters' level of
certainty regarding their vote choice. These results largely comport with our expectations regarding
the moderating impact of network composition on the effects of televised campaign advertising.
Consonant messages from candidates increase resistance to persuasion and help to strengthen
voters' resolve in terms of their candidate preferences when received within the context of a social
environment that is substantially devoid of conflict. General disagreement diminishes the impact of
consonant political ads to the point where even middling levels of discord wipe out the significance
of our ad effects.
We expected dissonant ads to produce marginal effects plots similar in appearance to those
detailed above, with increases in exposure to dissonant political advertisements having more of a
persuasive effect when respondents are situated within conflict-ridden social environments. That is,
when people are often confronted with disagreement in their interpersonal discussion network we
anticipated that dissonant messages from the mass media would prove to be more persuasive than if
they were encountered in isolation or in a social context devoid of disagreement. What we found
instead surprised us to an extent. As the plot displayed in Figure 2a demonstrates, only extreme
values of general disagreement (a score of five on a five-point scale) produce anything in the way of
a moderating influence on the persuasive effects of dissonant TV ads.
[Insert Figures 2a and 2b about here]
Instead of magnifying the persuasive impact of campaign advertising, though, a one standard
deviation increase in exposure to dissonant ads is actually associated with a modest decrease in the
predicted probability of shifting one's candidate preference at higher levels of general disagreement.
In the extreme case, that is, when dissonant ads are encountered within a social environment fraught
with conflict (a value of five on the general disagreement scale), advertising actually appears to
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strengthen respondents' resolve to vote for the candidate for whom they indicated their support in
wave nine of the survey. We expected to find that network disagreement enhances the persuasive
power of political advertising. Clearly this is not the case. The result that disagreement limits the
effectiveness of mass-mediated attempts at persuasion is not entirely without precedent. Druckman
and Nelson (2003), for instance, found that citizen deliberation curtails elites' ability to frame
political debates in accordance with their preferred interpretation.
We also find that an increase in exposure to dissonant advertising drives down the predicted
probability of growing more certain in one's initial choice of a presidential candidate. This effect is
tempered, however, by whether an individual's social network is punctuated by disagreement, as
those who encounter little to no disagreement in their social environment are the only ones who are
affected by dissonant messages from the mass media. Dissonant ads have no effect on vote certainty
when those exposed to such efforts at persuasion have a chance to deliberate with others. Although
the effect is not statistically significant, exposure to dissonant advertising conditioned on extreme
values of general disagreement is actually associated with increases in respondents' level of certainty
about their initial candidate choice. The plot displayed in Figure 2b documents this effect. Omitting
those who reported having no discussion partners from the dataset and re-estimating the same basic
model described above (albeit without an indicator tapping whether or not the respondent reported
talking with others during the campaign and any accompanying interaction terms) produces
estimates that are nearly identical to those reported here. These results are available upon request.
What of those who did not report having any discussion partners? According to Schmitt-
Beck (2003), individuals who do not discuss politics with anyone else present political elites with an
"open flank" through which mass-mediated attempts at persuasion can have an impact. We find little
evidence to this effect, however. As the plot displayed in Figure 3a shows, a one standard deviation
increase in exposure to dissonant ads decreases the predicted probability of persuasion among those
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without any discussion partners. Additionally, dissonant ads have no effect on how certain
respondents without social networks are about their chosen candidate (see Figure 3b).
[Insert Figures 3a and 3b about here]
Likewise, the effect of consonant advertising on persuasion is not moderated by the absence
of discussion partners (see the plot shown in Figure 4a). Increases in exposure to consonant
campaign ads do, however, have an impact on the strength of support for individuals' chosen
candidate in the absence of discussion, decreasing the predicted probability of growing more certain
about their candidate preference. Taken together, these results suggest that ads have little impact on
those who report not discussing politics, and where significant, have an effect that runs counter to
the candidates' presumed goals. That is, candidates are neither able to shore up support nor
persuade by using campaign advertising to reach those who are without discussion partners.
[Insert Figures 4a and 4b about here]
As an additional robustness check, we also estimated a separate model using observations
drawn from among the number of those who did not report talking to anyone during the campaign.
Interestingly, our results suggest that political advertising appears to have no effect whatsoever on
those who reported having no discussion partners (results not shown). The mere presence or
absence of interpersonal discussion thereby appears to provide yet another moderating influence on
the persuasion effects described by previous scholars (Franz and Ridout 2007, 2010; Huber and
Arceneaux 2007). It stands to reason that citizen talk during the campaign is necessary in order for
political ads to have any influence on voter preferences. Rather than representing an "open flank,"
then, through which mass mediated messages are able to pass unfettered, those who do not have
access to a discussion network are seemingly unaffected by political ads. As such, it appears that no
persuadable man (or woman) is an island.
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DISCUSSION AND CONCLUSION
We began this project with the intention of testing theories of how the structure of voters'
interpersonal discussion networks moderates the impact of the mass media on attitude change and
persuasion. Although the impact of the mass media has been a perennial concern for students of
campaigns (Berelson, Lazarsfeld, and McPhee 1954; Katz and Lazarsfeld 1955), we believe our study
represents the most complete test of the mechanisms through which citizens' discussion networks
enhance or diminish elites' efforts at using the mass media to persuade. Previous work has largely
been forced to make assumptions about which candidates were supported by particular news outlets
(though see de Vreese and Boomgaarden 2006). Our study, by contrast, circumvents this
shortcoming by employing measures of televised campaign advertising, as there is little chance that
ads aired by Obama during the 2008 campaign could be construed as supporting any other
candidate. The same can be said for McCain's advertising. Coupled with good measures of
disagreement in voters' interpersonal discussion networks, our data allow us to speak to the ways in
which social networks interact with messages received from the mass media to shape candidate
preferences.
In addition, we also contribute to recent work on the persuasive effects of campaign
advertising. A flurry of recent studies have uncovered evidence of a direct effect of political
advertising on persuasion (Brader 2005; Franz and Ridout 2007, 2010; Huber and Arceneaux 2007;
Johnston, Hagen, and Jamieson 2004). The persuasive power of campaign ads is hardly absolute,
however, as other factors have been shown to moderate their impact. Political awareness, for
instance, serves as a crucial moderator, with those who have middling levels of political awareness
being the most likely to be influenced by campaign ads. Here we contribute to this endeavor, and
help to chart the boundaries of ads' impact on the vote by examining how disagreement within
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individuals' social environments conspires to limit the effectiveness of mass-mediated attempts at
persuasion.
In many respects, our results are surprising, and lend only partial support to the most
canonical statements of the interactive relationship between personal and mass-mediated forces in
the context of the campaign. Individuals situated within more agreeable networks are more likely to
strengthen their candidate preferences and, correspondingly, resist shifting their support to a
different candidate when exposed to ads that are consonant with their initial vote choice. This
relationship comports well with what Katz and Lazarsfeld (1955) termed the "reinforcement
function" of the mass media (the "filter hypothesis" according to Schmitt-Beck 2003). And as
Nimmo writes, "to the extent that steadying the morale of supporters is vital to victory,
reinforcement is a prime objective of politicians" (1970, 165-166).
The observed effects of dissonant messages on voter certainty and persuasion, however,
follow a very different pattern. Disagreement within a network serves to limit, rather than enhance,
the persuasive effect of dissonant political advertising. Similarly, increases in exposure to dissonant
ads actually seem to foster greater degrees of uncertainty among individuals who are situated in
discussion networks that are devoid of conflict. There is little evidence that dissonant advertising has
any effect when encountered within a social environment studded with disagreement. While
inconsistent with the hypothesized "reinforcement function" of the mass media, such findings are
reminiscent of work by Druckman and Nelson (2003) which demonstrates how citizen deliberation
presents a barrier for elites, weakening their ability to frame the public debate in their preferred way.
Whereas they find that cross-cutting political talk moderates the impact of indirect media effects, here
we suggest that the direct impact of mass-mediated political communications is also subject to the
kinds of social forces that led the early Columbia studies to the verdict that the mass media has little
effect on the vote.
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At least one other finding from this study runs sharply counter to early theorizing regarding
the likely impact of interpersonal disagreement on preference strength and persuasion. Contrary to
Berelson, Lazarsfeld, and McPhee's (1954) classic treatment of the subject in Voting, partisan
differences within a voter's social network do not serve to moderate the impact of campaign
messages on the vote. Instead, and in line with more recent treatments of the effects of different
types of disagreement on political behavior (Klofstad et al. 2013), we find that general disagreement,
and not partisan network disagreement, serves to moderate the effect of mass-mediated attempts at
persuasion.
Not only do our results contradict longstanding findings in the study of campaigns, clarifying
the moderating effect of interpersonal communication on elites' efforts at persuasion, but they also
hold implications for candidate strategy. As of now it would seem difficult for campaigns to target
voters on the basis of the composition of their social environment. Effective means to glean
information on voters' social connections are likely beyond the campaigns' reach for the time being,
but may be on the horizon. Reports regarding the Obama campaign's efforts at microtargeting
voters through social media outlets suggest that it may not be too much of a stretch for future
presidential hopefuls to add social network composition to the list of demographic attributes that
they already use to identify persuadable voters. At this point it is important to remember that our
evidence is drawn from a single election. And while the confluence of advertising data with good
survey measures of network disagreement provides us with the clearest look to date at the interplay
of both the personal and impersonal communications that voters encounter during the campaign,
we must acknowledge the possibility that our results may be context-dependent. If our findings
generalize to other election contests, campaigns would do well to target supporters nestled within
agreeable networks while at the same time avoiding backers of the other party's nominee and those
who do not discuss politics with others.
19
Which brings us to one of the key shortcomings of our study. While ad "tonnage" may
influence voters' preferences at the margins, the content of those ads also matters. Certain messages,
without a doubt, resonate more strongly with particular subsections of the electorate than they do
others. Recent scholarship on microtargeting and persuasion (Hillygus and Shields 2008; though see
Sides and Karch 2008) serves to highlight this fact, and points to the necessity of connecting the
messages that elites' relay though the mass media to the discussions that take place over the course
of the campaign in citizens' interpersonal networks. Future work in this area ought to focus on the
conditions under which the content of the campaigns' televised appeals filters through voters' social
environment. Doing so would permit a more authoritative examination of Katz and Lazarsfeld's
(1955) expectations concerning the "relay function" of the mass media, and might also yield results
that have applications in the realm of campaign strategy and voter targeting.
20
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23
Table 1: Descriptive Statistics of Key Variables
Mean Standard Deviation
Median Minimum Maximum
Partisan Disagreement 1.11 1.33 0.67 0.00 6.00 General Disagreement 2.79 1.78 3.33 0.00 5.00 Dissonant Advertisements (in 1,000s)
0.39 0.56 0.01 0.00 2.74
Consonant Advertisements (in 1,000s)
0.38 0.54 0.00 0.00 2.68
Vote Change 0.03 0.64 0.00 -1 1
24
Table 2. The Moderating Influence of Network Composition on the Persuasive Effect of Televised Political Advertising
Variable Coeff.a. (S.E.)b.
General Network Disagreement
0.039 (0.077)
Partisan Network Disagreement
-0.048 (0.048)
No Discussion Partners
0.232 (0.384)
Consonant Ads (In Thousands of Airings)
1.422** (0.600)
Dissonant Ads (In Thousands of Airings)
-1.461** (0.708)
Dissonant Ads × Partisan Disagreement
0.061 (0.129)
Dissonant Ads × General Disagreement
0.383** (0.185)
Dissonant Ads × No Discussion
1.615** (0.749)
Consonant Ads × Partisan Disagreement
-0.025 (0.132)
Consonant Ads × General Disagreement
-0.362** (0.157)
Consonant Ads × No Discussion
-1.629** (0.714)
Cutpoint 1
-1.841 (0.580)
Cutpoint 2 0.899 (0.581) Number of Cases 2,240
-2134.18 Log Pseudolikelihood
**p<0.05; *p<.10. a. Cell entries are ordered logistic regression estimates. b. Standard errors are clustered by media market (195 clusters). The dependent variable is a three-category ordinal variable that ranges from -1 to 1. Respondents received a score of negative one if they moved toward supporting a different candidate in wave ten than they supported in wave nine of the study. Those receiving a score of zero (the modal score) did not change their candidate preference. A score of one was assigned to respondents who strengthened their support for the candidate for whom they indicated their support in the previous wave. The model also controls for changes in party identification between wave nine and wave ten, gender, age, age squared, race, employment status, income, education, ideology, TV news watching, and an indicator for whether the survey was administered on the day of a major campaign event (such as one of the debates).
25
01
23
45
-0.2-0.10.00.10.20.3
Fig
ure
1a: E
ffect of C
onsonant A
dvert
isin
g o
n P
ers
uasio
n
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
General Disagreement
Change in the Probability of Shifting Vote Preference
01
23
45
-0.2-0.10.00.10.20.3Fig
ure
1b: E
ffect of C
onsonant A
dvert
isin
g o
n P
refe
rence S
trength
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
General Disagreement
Change in the Probability of Strengthening Vote Preference
Each Estimate Represents the Impact of a One Standard Deviation Increase in Consonant Advertising
26
01
23
45
-0.2-0.10.00.10.20.3Fig
ure
2a: E
ffect of D
issonant A
dvert
isin
g o
n P
ers
uasio
n
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
General Disagreement
Change in the Probability of Shifting Vote Preference
01
23
45
-0.2-0.10.00.10.20.3Fig
ure
2b: E
ffect of D
issonant A
dvert
isin
g o
n P
refe
rence S
trength
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
General Disagreement
Change in the Probability of Strengthening Vote Preference
Each Estimate Represents the Impact of a One Standard Deviation Increase in Dissonant Advertising
27
-0.2-0.10.00.10.20.3
Fig
ure
3a: E
ffect of D
issonant A
dvert
isin
g o
n P
ers
uasio
n
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
Discussants No Discussants
Change in the Probability of Shifting Vote Preference
-0.2-0.10.00.10.20.30.4Fig
ure
3b: E
ffect of D
issonant A
dvert
isin
g o
n P
refe
rence S
trength
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
Discussants No Discussants
Change in the Probability of Strengthening Vote Preference
Each Estimate Represents the Impact of a One Standard Deviation Increase in Dissonant Advertising
28
-0.2-0.10.00.10.20.3
Fig
ure
4a: E
ffect of C
onsonant A
dvert
isin
g o
n P
ers
uasio
n
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
Discussants No Discussants
Change in the Probability of Shifting Vote Preference
-0.2-0.10.00.10.20.3Fig
ure
4b: E
ffect of C
onsonant A
dvert
isin
g o
n P
refe
rence S
trength
(Bars
Indic
ate
Sim
ula
ted 9
5%
Confidence Inte
rvals
)
Discussants No Discussants
Change in the Probability of Strengthening Vote Preference
Each Estimate Represents the Impact of a One Standard Deviation Increase in Consonant Advertising
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