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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

REFERENCES

Atwater, Tony, Michael B. Salwen, and Ronald B. Anderson. 1985. "Interpersonal Discussion as a Potential Barrier to Agenda-Setting." Newspaper Research Journal 6: 37-43.

Beck, Paul Allen. 1991. "Voters' Intermediation Environments in the 1988 Presidential Contest." Public Opinion Quarterly 55: 371-394.

Beck, Paul Allen, Russell J. Dalton, Steven Greene, and Robert Huckfeldt. 2002. "The Social Calculus of Voting: Interpersonal, Media, and Organizational Influences on Presidential Choices." American Political Science Review 96(1): 57-73.

Berelson, Bernard R., Paul F. Lazarsfeld, and William N. McPhee. 1954. Voting: A Study of Opinion Formation in a Presidential Campaign. Chicago: University of Chicago Press.

Brader, Ted. 2006. Campaigning for Hearts and Minds: How Emotional Appeals in Political Ads Work. Chicago: University of Chicago Press.

Campus, Donatella, Gianfranco Pasquino, and Cristian Vaccari. 2008. "Social Networks, Political Discussion, and Voting in Italy: A Study of the 2006 Election." Political Communication 25(4): 423-444.

Cho, Jaeho. 2005. "Media, Interpersonal Discussion, and Electoral Choice." Communication Research 32(3): 295-322.

Cho, Jaeho. 2008. "Political Ads and Citizen Communication." Communication Research 35(4): 423-451. Cho, Jaeho. 2011. "The Geography of Political Communication: Effects of Regional Variations in

Campaign Advertising on Citizen Communication." Human Communication Research 37: 434-462. Cho, Jaeho. 2013. "Campaign Tone, Political Affect, and Communicative Engagement." Journal of

Communication 63(6): 1130-1152. Cho, Jaeho, Dhavan V. Shah, Jack M. McLeod, Douglas M. McLeod, Rosanne M. Scholl, and

Melissa R. Gotlieb. 2009. "Campaigns, Reflection, and Deliberation: Advancing an O-S-R-O-R Model of Communication Effects." Communication Theory 19: 66-88.

Djupe, Paul A., Anand E. Sokhey, and Jacob R. Neiheisel. No date. "The Political Implications of Religious Change." Unpublished manuscript.

Druckman, James N., and Kjersten R. Nelson. 2003. "Framing and Deliberation: How Citizens' Conversations Limit Elite Influence." American Journal of Political Science 47(4): 729-745.

Erbring, Lutz, Edie Goldenberg, and Arthur Miller. 1980. "Front-Page News and Real-World Cues: A New Look at Agenda-Setting by the Media." American Journal of Political Science 24(1):16-49.

Finifter, Ada W. 1974. "The Friendship Group as a Protective Environment for Political Deviants." American Political Science Review 68(2): 607-625.

Franz, Michael M., Paul Freedman, Kenneth M. Goldstein, and Travis N. Ridout. 2008. Campaign Advertising and American Democracy. Philadelphia, PA: Temple University Press.

Franz, Michael M., and Travis N. Ridout. 2007. "Does Political Advertising Persuade?" Political Behavior 29(4): 465-491.

Franz, Michael M., and Travis N. Ridout. 2010. "Political Advertising and Persuasion in the 2004 and 2008 Presidential Elections." American Politics Research 38(2): 303-329.

Freedman, Paul, and Ken Goldstein. 1999. "Measuring Media Exposure and the Effects of Negative Campaign Ads." American Journal of Political Science 43(4): 1189-1208.

Gerber, Alan S., Gregory A. Huber, David Doherty, and Conor M. Dowling. 2012. "Disagreement and the Avoidance of Political Discussion: Aggregate Relationships and Differences Across Personality Traits." American Journal of Political Science 56(4): 849-874.

Granovetter, Mark S. 1973. "The Strength of Weak Ties." American Journal of Sociology 78(6): 1360-1380.

Hillygus, D. Sunshine, and Todd G. Shields. 2008. The Persuadable Voter: Wedge Issues in Presidential Campaigns. Princeton, NJ: Princeton University Press.

21

Huber, Gregory A., and Kevin Arceneaux. 2007. "Identifying the Persuasive Effects of Presidential Advertising." American Journal of Political Science 51(4): 957-977.

Huckfeldt, Robert , Paul E. Johnson, and John Sprague. 2004. Political Disagreement: The Survival of Diverse Opinions within Communication Networks. New York: Cambridge University Press.

Huckfeldt, Robert, and John Sprague. 1995. Citizens, Politics, and Social Communication: Information and Influence in an Election Campaign. New York: Cambridge University Press.

Iyengar, Shanto, and Donald R. Kinder. 1987. News that Matters: Television and American Opinion. Chicago: University of Chicago Press.

Johnston, Richard, Michael G. Hagen, and Kathleen Hall Jamieson. 2004. The 2000 Presidential Election and the Foundations of Party Politics. New York: Cambridge University Press.

Kam, Cindy D., and Robert J. Franzese, Jr. 2007. Modeling and Interpreting Interactive Hypotheses in Regression Analysis. Ann Arbor: University of Michigan Press.

Katz, Elihu, and Paul F. Lazarsfeld. 1955. Personal Influence: The Part Played by People in the Flow of Mass Communication. New York: The Free Press.

Klofstad, Casey A., Anand Edward Sokhey, and Scott D. McClurg. 2013. "Disagreeing about Disagreement: How Conflict in Social Network Affects Political Behavior." American Journal of Political Science 57: 120-134.

McClurg, Scott D. 2004. "Indirect Mobilization: The Social Consequences of Party Contacts in an Election Campaign." American Politics Research 32(4): 406-443.

McCombs, Maxwell E., and Donald L. Shaw. 1972. "The Agenda-Setting Function of Mass Media." Public Opinion Quarterly 36(2): 176-187.

Mendelsohn, Matthew. 1996. "The Media and Interpersonal Communications: The Priming of Issues, Leaders, and Party Identification." Journal of Politics 58(1): 112-125.

Mondak, Jeffery J. 1995. "Media Exposure and Political Discussion in U.S. Elections." Journal of Politics 57(1): 62-85.

Mutz, Diana C., and Jeffery J. Mondak. 2005. "The Workplace as a Context for Cross-Cutting Political Discourse." Journal of Politics 68(1): 140-155.

Newton, Kenneth. 2006. "May the Weak Force be with You: The Power of the Mass Media in Modern Politics." European Journal of Political Research 45(2): 209-234.

Nimmo, Dan. 1970. The Political Persuaders: The Techniques of Modern Election Campaigns. Englewood Cliffs, NJ: Prentice-Hall.

Pan, Zhongdang, Lijiang Shen, Hye-Jin Paek, and Ye Sun. 2006. "Mobilizing Political Talk in a Presidential Campaign." Communication Research 33(5): 315-345.

Patterson, Thomas E., and Robert D. McClure. 1976. The Unseeing Eye: The Myth of Television Power in National Elections. New York: G.P. Putnam's Sons.

Schmitt-Beck, Rüdiger. 2003. "Mass Communication, Personal Communication and Vote Choice: The Filter Hypothesis of Media Influence in Comparative Perspective." British Journal of Political Science 33: 233-259.

Shaw, Daron R. 2006. The Race to 270: The Electoral College and the Campaign Strategies of 2000 and 2004. Chicago: University of Chicago Press.

Sides, John, and Andrew Karch. 2008. "Messages that Mobilize? Issue Publics and the Content of Campaign Advertising." Journal of Politics 70(2): 466-476.

Tomz, Michael, Jason Wittenberg, and Gary King. 2003. CLARIFY: Software for Interpreting and Presenting Statistical Results.

de Vreese, Claes H., and Hajo G. Boomgaarden. 2006. "Media Message Flows and Interpersonal Communication: The Conditional Nature of Effects on Public Opinion." Communication Research 33(1): 19-37.

22

Wanta, Wayne, and Yi-Chen Wu. 1992. "Interpersonal Communication and the Agenda-Setting Process." Journalism & Mass Communication Quarterly 69(4): 847-855.

Zaller, John R. 1992. The Nature and Origins of Mass Opinion. New York: Cambridge University Press.

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