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Political Framing Over Time: The Effect of Individuals’ Need-To-Evaluate

By Jonathan Webber Advisor: Jamie Druckman

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I. Abstract

One of the main purposes of political science is to study the interaction of

political elites and the public. Understanding how elites affect individual decision

making through a combination of providing “cues” in the form of endorsements to

individuals and “framing” issues presented to the public is vital in understanding our

political system. Within the field of political framing, there has been much research on

the immediate effects of frames and cues separately, but little done on their interaction,

and even less done on how this interaction gains or loses influence over time.

Individuals are constantly being exposed to varying frames and cues, so looking

at the effect of time on how these stimuli affect an individual’s political opinion-making

is an important aspect of the political framing field that has so far been under-examined.

Using the results from an experiment I completed with a team at Northwestern

University during Winter 2008, I examine the effect of time on the influence of frames

and cues. Our experiment includes data at multiple points in time, allowing a time

analysis to be completed. I look specifically at which individual opinion-making

attributes influence whether or not frames and cues will have long-standing effects on

opinion-formation, and I find that opinion-making attributes can significantly influence

the impact of frames and cues interacting over time.

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II. Introduction

Democracy involves the public formulating opinions and translating them to

government officials who attempt to respond to public opinions. Therefore,

understanding the nature of public opinion is critical. Examining how the media and

politicians affect public opinion, and then how public opinion in turn affects political

decisions, is essential in understanding how our representative democracy operates.

Scholars have spent much time studying many different aspects of these issues.

Within the field working to examine what influences individual decision making and

opinion formation, much of the focus has been on one of two things: A) how political

elites provide ‘cues’ to shape opinion formation, or B) how political elites ‘frame’ issues,

campaigns, news items, etc. Much of the focus for both areas has been in a snap-shot

view fashion, meaning examining the effect at an individual point in time instead of over

a period of time. What I will examine in this paper is how cues and frames interact, and

how their interaction, along with individual decision-making characteristics, affects

opinion formation over time. There has not been sufficient research done in either the

interaction of cues and frames, nor in their effect over a period of time.

Examining the effect of time is an important and essential aspect of developing a

comprehensive theory of the effect of media framing and campaign cues on political

opinion formation in voters. It is not possible to analyze the true effect of a frame or a

cue in a snapshot of time – for the realities of campaigns are not like that at all. In real-

life campaigns, all the candidates as well as their staff, their surrogates, local and

sometimes national media, political action committees and other organizations, and

voters themselves communicate in a back-and-forth over many weeks or months. It is

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certainly important to understand the immediate effect of a stimulus frame or cue at a

particular time, but also important to understand the effect of its placement both on the

timeline of a campaign and also in relation to other competing frames on that timeline.

The true effect of an individual frame or cue in a campaign is very difficult to

identify, which is why most researchers and studies trying to understand their effect

default to looking at opinion changes in respondents immediately after exposure. This

approach, however, misses many of the realities and important determining factors of

campaigns. For one, the effectiveness of a frame may not be constant across time. Some

arguments, types of arguments, or loudness of arguments may be much more successful

at the start of a campaign as compared with during a get-out-the-vote attempt. Some may

require repetition over time, or only be effective when packaged with a variety of other

frames or cues presented at other times – as part of a pattern of argumentation or

information. Some may have an effect right away but then diminish in importance; while

for others the effect may not emerge until some unit of time has passed. All in all, a

snapshot cannot capture comprehensively the impact of a media or political elite frame or

cue.

Because of the difficulty in studying the complex, detailed realities of opinion

formation based on mass information consumption over a large amount of time, it is

suggested in the literature that a good place to start is thinking about the ability of

individuals to learn and retain information over a period of time (Druckman and Chong,

n.d.). Looking at how individuals learn and remember information during a campaign

will be helpful in determining the long-term effect of an instance of exposure to a

political frame or cue. My work focuses on this question, and specifically whether

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individual personality differences in forming evaluative opinions of candidates affect the

long-term retention of information. Through use of a ‘need-to-evaluate’ indicator of

individual opinion formation, I evaluate the results of t a lab experiment to learn how

individuals making on-line evaluations learn and retain information about a campaign, as

compared to those who use memory-based processing and have a lower need-to-evaluate

score. The need-to-evaluate indicator and affiliated memory types will be explained in

depth later. Our lab experiment and my subsequent research are designed to help begin

to answer the following questions:

1. How do individuals process cues and frames over time?

2. What individual differences moderate this processing?

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III. Literature Review Frames and Cues A political attitude is an evaluation of an object, such as a candidate or political

issue. In political science the two main influencers of political attitudes and attitude

formation are frames and cues, and I will start by discussing each in turn. Frames refer to

emphasis of a particular argument about an issue; cues refer to a political elite’s

endorsement of one side on an issue.

Political scientists have long acknowledged that individuals often do not know

much about politics (e.g. Delli-Carpini and Keeter, 1996). To compensate for this,

individuals often rely on simple cues from political elites such as endorsements (e.g.

Downs 1957, Popkin 1991, Lupia and McCubbins 1998, Lau and Redlawsk 2006).

When deciding a political opinion, individuals may have a thorough understanding of an

issue or set of candidates and thus look to political elites for help in the form of listening

for endorsement cues. It is has been clearly shown that individual voters often rely on

these cues to fill information gaps when creating or changing political opinions, although

influence of endorsement cues certainly changes due to attributes like loudness,

repetition, and trustworthiness of the source.

Frames have also been shown to affect political opinions. Frames differ from

cues because they tell people what dimensions are salient, or in other words how to think

about a particular issue. Dennis Chong (1993) describes framing as the “essence of

public opinion formation.” Framing is the primary way of elites influencing an

individual’s political opinion formation for a particular issue. According to Druckman

and Nelson (2003), a “framing effect occurs when in the course of describing an issue or

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event, a speaker’s emphasis on a subset of potentially relevant considerations causes

individuals to focus on these considerations when constructing their opinions.” The slant

in which they present an issue or event is the framing event, which they hope will be

salient for those consuming the information.

The most commonly used example in the political framing literature is about how

a hate-rally can be viewed. The light in which a speaker, newspaper, group or individual

presents the rally can have significant effects on how others create their opinion on

whether it should be allowed or not (Druckman 2001). The rally could be framed as a

free speech issue, leading citizens to focus on speech considerations, thus being more

likely to support allowance of the rally to take place. Or, the rally could be framed as a

public disturbance/safety issue, leading citizens to be more likely to oppose such a rally

based on possible safety implications. Multiple studies have found that contrasting these

frames in an asymmetric study show statistically significant effects of the different

approaches to framing the hate-rally issue (e.g., Nelson, Clawson, and Oxley 1997).

There are numerous other examples of the importance of framing – practically

every political or policy issue provides a solid example. Advocates of abortion rights are

‘pro-choice’ whereas opponents consider themselves ‘pro-life.’ Each group frames itself

in a positive light, and the opposite in a negative light. Opponents of abortion, for

example, label abortion rights advocates as ‘pro-abortion,’ which carries a strong

negative connotation. Another example is that advocates of laws allowing employees at

unionized workplaces to always be allowed to opt-out of union dues call the issue ‘right

to work,’ while opponents who believe the efforts are intended to diminish the power of

unions to collectively bargain for higher wages and better work conditions refer to the

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laws as ‘right to work for less.’ Social security, the war in Iraq, and affirmative action

are other volatile political issues in which argument framing is pivotal and has huge

opinion implications.

Framing studies have been done in a number of different areas (e.g. Li 1998,

Levin et al 1998, Camerer 1995, Zaller 1992, Tversky and Kahneman 1981, Cobb and

Kuklinski 1997). Studies have been done on the interaction between frames and

individuals’ values, on the effect of frame repetition, on the strength of frames and their

corresponding change in effect on opinions, and many other areas. Framing affects

campaigns in many ways, such as attempting to push voters toward focusing on issues or

frames in a campaign. Some candidates are advantaged when individuals focus on

specific policy issues, whereas others are advantaged by individuals looking at candidate

personality and stylistic differences (Druckman and Holmes 2004).

How frames function when competing is another important area of study. The

study of frames competing with each other in a variety of ways has been the subject of

increasing research in the last several years (Sniderman and Theriault 2004, Druckman

and Chong 2007). In 2004, Sniderman and Theriault wrote “framing studies . . . have

neglected the fact that frames are themselves contestable. They have instead restricted

attention to situations in which citizens are artificially sequestered, restricted to hearing

only one way of thinking about a political issue.” Several recent studies have focused on

the impact of time on frame effects, which is also an area of focus for this thesis.

What is clear from past research is that individuals’ opinions and process of

opinion formulation can certainly be affected by political elites and media

communications. The common result of many snap-shot, single frame exposure

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experimental studies has been that respondents’ opinions are likely to reflect the frame to

which they have been exposed. These studies are the first step towards researchers’

development of a comprehensive framing theory, but they ignore many important issues

such as frame persistence, interaction with cues, placement among other frames in a

competitive environment, individual personality differences, strength and loudness of

frames, and others.

Over-Time Effects

In the same way that Sniderman and Theriault (2004) argued that studies

overlooking frame competition do not adequately explain the effect of frames, studies

that fail to include an aspect of time may not be able to adequately gauge the true

effectiveness of particular frames and cues. There have not been any published studies in

contemporary political science looking at the affect of cues over-time, although there is

some older work in psychology (Hovland and Weiss 1951-52). There have been three

main studies looking at framing over time (Druckman and Nelson 2003, Tewksbury et al

2000, de Vreese 2004), and all three suggest a strong effect of time on the influence of

frames. Several of these studies have suggested relatively short-lived frames, meaning

over time the influence of the frames have decreased. No study has looked at frames vs.

cues over time, nor how individual decision-making attributes affect these frame/cue

interactions over time, which is the area that I focus on in this thesis.

It is important to put the issue of time in context. A particular media frame or

elite cue is presented to the public, or a particular respondent, at a time t. That time is

after t=0 which is the beginning of the campaign (and at which time preconceptions must

be taken into account), and before the time of the election. At any given time t, there

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may be 0, 1, or multiple frames or cues interacting. And the effect of any frame or cue

presented at time point t is determined partially by what comes before and after t in the

campaign, in addition to the strength, loudness, and repetition of that frame.

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IV. Need-to-Evaluate Moderator The area I will focus most on is on individuals’ “need-to-evaluate” (Bizer et al

2004, Bizer et al 2005,Tormala and Petty 2001, Frederico and Schneider 2007).

Specifically, I will look at the effect that need-to-evaluate (NE) has both on short and

long term effects of framing and cues. According to Bizer et all (2004), need-to-evaluate

is “an individual difference variable that measures the extent to which people

spontaneously evaluate objects or experiences as either good or bad.” Put simply, those

with a high need-to-evaluate will quickly evaluate or create attitudes towards things, and

are more likely to have opinions on a wide variety of issues. Individuals with a lower NE

are less likely to evaluate, and will have fewer opinions overall than those with high NE.

Individuals with high NE develop opinions and evaluations more spontaneously than

those with low NE. Individuals with a high NE are said to form attitudes on-line, so

when asked to make a judgment on something from the past, they will think back to what

their attitude or opinion was then, rather than coming up with a new opinion on the spot

after thinking back on memories. Individuals with low NE are said to be memory-based

processors, basing decisions and evaluations on remembering situations.

In 2004, Bizer et al wrote a paper looking at the need-to-evaluate moderator’s

effect on an individual political decision-making process. To do so, they analyzed data

from the 1998 and 2000 National Election Survey. They found that the effects of the

need-to-evaluate moderator went far beyond solely holding more opinions. It affected

both how opinions were made as well as correlated with a number of other individual

characteristics. They found high NE individuals more likely to use party ID or issues

stances in forming political opinions, and that NE in individuals was connected with the

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likelihood that they participate in political activism and with their news media

consumption habits. Bizer et al suggest that there are cognitive, behavioral, and affective

effects of the NE moderator that affect political activity and opinion formation for

individuals. This leads to the general expectation that high NE individuals will maintain

opinions formed from one time to the next, while low NE will not, and instead will base

their future opinions on what information they can remember.

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V. Description of Experiment

I use data from an experiment completed at Northwestern University by a team

including Professor Jamie Druckman and myself. We conducted the experiment in

Winter 2008, and it was done in two parts. The first part consisted of a 45-minute in-

person study, and the second part consisted of a 10-minute online follow-up conducted

approximately two weeks later. I assisted with Part 1 of the experiment, and fully

conducted Part 2. We had 416 individuals participate in the first portion of the study, and

359 of them also complete the follow-up several weeks after.

Part 1

The beginning of Part 1 of the experiment consisted of gathering background data

from the respondents. After that, respondents were given some basic information about a

Republican primary for a US House seat from Massachusetts in a 2007 special election.

The two candidates in the Republican primary were Tom Tierney and Jim Ogonowski.

Photos of the candidates were distributed to help respondents from confusing the two.

Next, respondents were exposed to an article said to be from The Boston Globe.

There were nine (9) different versions of this article, varying in two dimensions – cues

and frames. On the cue dimension – the article either stated endorsements for Tierney,

endorsements for Ogonowski, or had no mention of any endorsement. For the conditions

which mentioned endorsements of Tierney, the newspaper article stated that, “The

campaign has recently attracted substantial attention because, somewhat surprisingly,

Meehan, the departing representative, came out in support of Tierney, even over the

candidates from his own Democratic party. Several other prominent Democrats, as well

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as the state Republican Party, have also endorsed Tierney.” The articles that discussed

endorsements of Ogonowski read the same except with Ogonowski’s name.

For the frame dimension, the news articles either included an “issue frame,” an

“image frame,” or no frame. The issue frame for articles was a paragraph that discussed

the main issues analysts expected the campaign to focus-on, and quoted a political

observer saying, “This election is about the issues such as the war and healthcare – the

voters need to determine who will put their preferences into action.” The image frame

for articles was a paragraph discussing the importance of personal differences between

the candidates, and quoted the same political observer saying, “The candidates share

similar outlooks on the issues, but they substantially differ in terms of their backgrounds

and capabilities. This election is about the candidates’ personal strengths and

weaknesses.” The ‘no frame’ articles do not comment on what the election should or

would focus on. In short, articles with the issue frame encouraged individuals to base

their opinions on issues like the war and healthcare, while articles with the image frame

encouraged individuals to base their opinions on personal candidate characteristics like

experience and capabilities. The articles with no frames did not encourage individuals to

base their opinion in any way.

The nine conditions came from a 3 x 3 matrix of all combinations of the three cue

possibilities and the three frame possibilities.

Table 1 – Condition matrix for round-one Ogonowski Cue Tierney Cue No Cue

Issue Frame 1 2 3 Image Frame 4 5 6 No Frame 7 8 9

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Following the provided Boston Globe article, respondents watched a 20-minute

clip of a debate between Tierney and Ogonowski, and then answered another set of

questions. The questions included asking respondents who they believe won the debate,

who they would have voted for, how the candidates compared on issues such as honesty

and knowledge, how the candidates as well as the respondent felt on a variety of political

issues such as healthcare or the Iraq war, and a variety of questions to determine how

much the respondent remembered factually from the news articles and video clips.

The first set of questions at the very beginning of the experiment helped identify

important personality, demographic, and interest qualities of the respondent. The

questionnaire asked three questions to measure individuals’ need-to-evaluate (NE). In

the original political science research, the need-to-evaluate measure consisted of 16

questions, but due to the prohibitive length, recent experiments have used three questions

to measure need-to-evaluate using response scales (Bizer et al, 2004). For our measure of

NE, we used the same three questions as those used by Bizer et al in their 2004 studies

involving the 1998 and 2000 National Election Survey (NES) Pilot Study. We also

scored individuals’ NE levels the same way Bizer et all (2004) did. Those three

questions are below, with coded scores in parenthesis after each answer option:

Some people have opinions about almost everything; other people have opinions about just some things; and still other people have very few opinions. What about you? Would you say you have opinions about almost everything, many things, some things, or very few things? Answers: Almost everything (1.0), many things (.66), some things (.33), very few things (0). Compared to the average person, do you have far fewer opinions about whether things are good or bad, somewhat fewer opinions, about the same number of opinions, somewhat more opinions, or far more opinions? Answers: Far fewer opinions (0), somewhat fewer opinions (.25), about the same (.5), somewhat more opinions (.75), far more opinions (1.0).

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Some people say it is important to have firm opinions about lots of things, while other people think it is better to remain neutral on most issues. What about you? Do you think it is better to have firm opinions about lots of things or to remain neutral on most issues? Answers: Firm opinions (1.0), remain neutral (0).

An index of respondents’ NE was developed by averaging the three scores, so 1 is

the maximum of the index and 0 the minimum. This moderator will be explained further

in the analysis portion later.

Part 2

Part 2 of the experiment consisted of contacting respondents two weeks after the

initial experiment and asking them to take part in a 5-10 minute follow-up. We

conducted the follow-up online, and it consisted of having the respondents fill out a

questionnaire via e-mail and send it back to us. After briefly reminding individuals of the

candidates, we ask them to respond to 26 questions – most of which were exactly the

same as questions asked during part 1 of the experiment. We started by asking if the

respondents have accessed any information about the election since Part 1 of the

experiment, and almost all responded that they had not, thus ensuring that our data was

not effected by frames/cues or other information not presented in Part 1 of the study. We

also asked if their media consumption habits had been normal in the past several weeks.

The questions repeated from Part 1 included questions about who the respondents

believed to have won the debate, who they would have voted for, where the candidates’

positions fell on a range of issues, a thermometer rating for the respondent’s feeling

toward the candidates, and whether the respondent remembered if either of them had

been endorsed by republicans and democrats.

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The questions were designed to provide us insight into how much the respondent

remembered from Part 1 of the study – and specifically which areas they remembered

most about. Questions were also asked about the respondent’s own political leanings to

track their opinions over time. Out of the 416 participants in Part 1, we were able to

gather data from 359 of them for the follow-up portion of the experiment. Data was then

matched using individual ID numbers from Part 1 to Part 2, to enable time-series

regression analysis to be completed.

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VI. Hypotheses of Results

Based on previous literature about need-to-evaluate as well as that on framing and

cues, there are several anticipated results from our study:

Hypothesis #1: There is no difference in effectiveness of frames and cues for low vs.

high NE after the initial exposure.

I predict that individuals with a low NE as compared with a high NE will not be

significantly different in how they are affected by the frames and cues in round-one. That

is, directly after initial exposure, the effect of individuals making a quick evaluation as

opposed to individuals thinking back on the very recent stimuli will not yield

significantly different effects from frames or cues.

Hypothesis #2: Individuals with high NE are more likely to be consistent on candidate

preference over time.

I expect that the time effect will be more exaggerated for memory-based

processors than on-line processors. Individuals with a low need-to-evaluate and who

process in a memory-based manner will be less likely to be consistent on opinion

formation than high need-to-evaluate on-line processors. One explanation for this is that

individuals with low NE will rely on their debate information recall in making their

round-two decision, whereas individuals with a high NE will directly recall their round-

one decision.

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Hypothesis #3: Cues will more significantly impact round-two decisions for low NE

individuals than will frames.

I predict that cues will play a more significant role in round-two decisions (after

controlling for round-one decisions) because cues are more easily and directly

remembered after a two-week lag than are frames, which point individuals towards

candidates less directly.

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VII. Results Results Overview

Before discussion of the results in comparison to the hypotheses, it is important to

present general results from rounds one and two of our study. All portions of the study

were completed in Winter 2008. As stated above, we had 416 individuals complete the

first round of the study. There were nine different study conditions, each completed by

approximately the same number of individuals (~46). Two weeks after the initial study,

participants were asked to complete in a ten-minute questionnaire, which we refer to as

‘round-two’ of the study. 359 of the 415 initial respondents completed round-two, and

almost all reported that they did not access additional information about the campaign in

the approximately two weeks between study rounds.

Voter choice is the best indicator of preference, and correlates highly with the

thermometer scores give to candidates as well as the determination of who won the

debate, so that is the indicator that we focus on for most of this analysis. This is rated on

a 1-7 scale, with the higher end being those more likely to vote for Tierney and the lower

end being those more likely to vote for Ognowski. A response of 1 means the respondent

strongly prefers Ognowski, a 2 means medium preference towards Ognowski, and a 3

means weak preference for Ognowski. A response of 4 means the respondent is

completed undecided, and a 5, 6, or 7 shows preference towards Tierney. Because the

variable we use to show voter preference is not dichotomous, we utilize OLS multiple

variable regressions and not loglinear regressions for our analysis throughout the paper.

Results are robust to using OLS rather than an ordered probit model. Below is the

distribution of responses for round-one and round-two candidate preference.

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Table 2 – Distribution of vote-preference in round-one Ranking Score Frequency Percent

Strong Ognowski 1 61 14.7% 2 64 15.4% 3 59 14.2%

44.3%

Tie 4 62 14.9% 5 64 15.4% 6 49 11.8%

Strong Tierney 7 56 13.5% 40.7%

Table 3 – Distribution of vote-preference in round-two Ranking Score Frequency Percent

Strong Ognowski 1 51 14.2% 2 66 18.3% 3 48 13.4%

46.0%

Tie 4 45 12.5% 5 51 14.2% 6 58 16.2%

Strong Tierney 7 40 11.1% 41.5%

The means and standard deviations of each vote-preference distribution are

below, and it is also important to note that the correlation between first and second time

vote choice opinion is .53, which is significant. The means and standard deviations show

that, overall, the distributions are quite similar.

Table 4 – Comparison of vote-choice distributions for rounds Study Round Mean Std. Dev.

Round-one 3.90 1.98 Round-two 3.87 1.98

Overall Analysis

We will look at a variety of independent variables to analyze the main dependent

variable, vote choice. Within the differences in conditions, we will look at the effect of

individuals receiving image versus issue frames, as well as the effect of those receiving

varying cue information. The different cues, and the text of each of the two frames, were

presented earlier. To refresh, in the news articles respondents read, some individuals’

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articles included an endorsement for Tierney (Tierney cue), an endorsement for

Ognowski (Ognowski cue), or no endorsement (no cue). Additionally, articles either

stated that the election was most about issues like Iraq and healthcare (issue frame), that

it was most about personality differences like experience (image frame), or gave no

statement on what the race was most about (no frame).

Through first looking at the responses to initial questions asked to respondents, it

appears that Tierney is advantaged on issue evaluations and Ogonowski is advantaged on

image evaluations. These results are found when looking at all respondents (which

differing conditions are hoped to all even out), as well as when looking specifically at

condition 1 – which are respondents receiving no cue and no frame information – the

main control group.

Looking specifically at cues we found no significant cue effect on vote choice,

although as anticipated, endorsement cues for candidates did not hurt them – the cues

pushed the average opinions in the expected directions, but not significantly. Although

there was some effect of the cue, cues did not trump all of the other factors in decision-

making. In other words, individuals did not simply follow the cues over all the other

information and frames presented. When looking more specifically at whether cues

influenced respondents’ opinions on issues or images of the candidates, there are several

interesting observations.

The critical regression shows round-one vote on exposure to the Tierney cue,

Ognowski cue, issue frame, or image frame. The regression is shown below, and it

shows the impact of the different stimuli across conditions. The results reveal that the

cues do not have significant effect on round-one opinion making, while both the image

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and issue frames do. And, as expected, the issue frame is significant in pushing votes

towards Tierney, and the image frame has a significant negative effect, pushing votes

towards Ognowski.

Regression #1 – Round-one opinion for all respondents Regress Round_1_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue .28 .24 1.18 0.24 Ognowski Cue -.28 .23 -1.18 0.24 Issue Frame .42 .23 1.79 0.07* Image Frame -.44 .23 -1.88 0.06* Constant 3.91 .21 18.47 0.00 N = 415 R2 = .045 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

We now do a similar regression for round-two opinion of all respondents on the

four different stimuli. Because the vast majority of respondents did not access additional

information about the Tierney – Ognowski election after round-one, we can begin to see

the effect of frames and cues two weeks after initial exposure to respondents.

Interestingly, in this regression the two cues are significant (both at a 95% level), and

neither the issue or image frame is significant – although both are close to being

significant at the 90% level. The cues are significant in the expected direction, with the

Tierney cue in the positive (Tierney) direction, and the Ognowski cue in the negative

(Ognowski) direction. And, although only marginally significant, the issue and image

frames also seem to work in the anticipated direction – with the issue frame exposure

pushing respondents towards Tierney, and the image frame exposure pushing respondents

down towards Ognowski.

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Regression #2 – Round-two opinion for all respondents Regress Round_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue .96 .24 4.03 0.00*** Ognowski Cue -.71 .24 -2.92 0.00*** Issue Frame .35 .23 1.51 0.13 Image Frame -.39 .24 -1.65 0.10 Constant 3.77 .22 17.29 0.00 N = 359 R2 = .148 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

While regression #2 shows an effect of all four stimuli, and the cues in particular,

on voting in round-two, it immediately raises the question of what role individuals’

round-one vote played in their round-two decision. In other words, are individuals

making their decision in round-two based on what they decided in round-one? Are they

going through the same decision-making thinking as they did in round-one? Or are the

frames and/or cues having some additional and different effect on respondents in the

follow up? To test the effect, we run an additional regression on respondents’ round-two

opinion, with the same independent variables as before, except this time additionally

regressing on the respondents round-one opinion score.

Not surprisingly, the round-one vote is highly significant, indicating that how

respondents voted in round-one strongly affected their round-two decision. Also

interesting, however, is the effect that inclusion of the round-one variable has on the

significance of frames and cues. Inclusion of the round-one variable renders the frames

much more insignificant as compared to regression #2 above. This shows that the

significance of the issue and image frames on round-two opinion is working almost

entirely through their initial impact on round-one decision making. However, the results

show that the cues are still both highly significant – both at the 99% level – indicating

that the cues seem to have re-emerged during round-two to have an independent and

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additional impact. At the end of the next section, we will analyze how the regression

functions when broken up into the two need-to-evaluate groupings.

Regression #3 – Round-two opinion for all respondents Regress Rd_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Rd.1 Vote Variables Coef. Std. Error T P>|t| Tierney Cue .79 .21 3.85 0.00*** Ognowski Cue -.62 .21 -3.00 0.00*** Issue Frame .17 .20 0.88 0.38 Image Frame -.16 .21 -0.76 0.45 Rd. 1 Vote 0.49 .04 11.27 0.00*** Constant 1.87 .25 7.42 0.00 N = 359 R2 = .374 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

Through analyzing the results of all respondents, there are several interesting

patterns that emerge. The first is the strong impact of frames during round-one combined

with a weak showing by cues in round-one, followed by a reversal of roles in round-two

for frames and cues. It appears that cues do not have a significant affect on voting

behavior when there is significant other information (the news article and the debate

video) being shown immediately prior to voting. However, they have a much stronger

effect after several weeks pass by and the details of the election scenario no doubt

diminish substantially in the minds of respondents.

Second, as anticipated, the effect of the frames on round-two decision making

decreases substantially when including round-one decision as an independent variable in

regression #3. The frame works much more subtly as a cue, so it is predictable that after

a two-week lag period how a person ended up deciding might be more of an indicator on

their next decision than the frame. Both of these observations will be discussed more

thoroughly after an analysis of the results using the need-to-evaluate moderator.

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“Need-to-Evaluate” Groupings

As discussed previously, the need-to-evaluate indicator will be used frequently in

our analysis, and was computed in the same way Bizer et al. (2004) did. It is created by

combining three questions asked in round-one about an individual’s decision making

habits. Once individual NE scores were calculated and scored on a 0 to 1 weighted scale,

we completed several tests to show our data is similar in terms of NE results to that of

Bizer et al.’s. They reported a .23 correlation between NE score and general political

knowledge (calculated by creating a weighted variable combining the many questions

asked in round-one about political knowledge and consumption habits), and our similar

correlation is .21. We also found that the three on-line items combined into one score

have an alpha value of .65, which is sufficiently high to combine into one construct. For

analysis purposes, respondents will be split into ‘high NE’ and ‘low NE’ groups based on

which side of the median their NE score falls on. There were 212 individuals classified

as low NE, and 199 classified as high NE.

Before presenting results and conclusions, it is also necessary to look at how the

two groupings of NE scores compare on vote choice. We find that, overall, low and high

NE individuals do not significantly differ on vote choice at either round-one or round-

two. Means and standard deviations for the rounds are shown below. Completed t-tests

(included in full as Appendix #1) show that we can fail to reject the null hypothesis that

the means of the two groups are different for both round-one and round-two. This

observation is essential, because if we rejected the hypothesis that vote choice was the

same, we would not be able to compare the significance of variables across different

regression groups based on the NE group.

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Round One Round Two

Group Mean Standard Dev. Mean Standard Dev.

Low NE 3.85 1.94 3.80 1.95

High NE 3.94 2.02 3.90 2.01

Overall 3.90 1.98 3.85 1.97

NE Analysis

In the “Overall Analysis” section above, we regressed round-one vote on

exposure to the four different stimuli (the two cues and two frames), and found that

overall the cues did not seem to have a significant effect on round-one opinion, but the

two frames did – the issue frame effect being positive (pushing respondents toward

Tierney) and the image frame effect being negative (pushing respondents toward

Ognowski). We now look at the same regression for round-one only, but this time

separated for the low NE and high NE groups. As can be seen in the results, as with the

first overall regression, neither group is impacted significantly by the cues in round-one.

Additionally, we can observe that only the image frame affected the low on-line group

significantly, and only the issue frame affected the high on-line group significantly.

Regression #4 – Low NE group for Round-one opinion Regress Round_1_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue .32 .34 0.94 0.35 Ognowski Cue -.32 .31 -1.01 0.31 Issue Frame .13 .32 0.41 0.68 Image Frame -.72 .32 -2.27 0.02** Constant 4.09 .27 13.81 0.00 N = 212 R2 = .054 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

28

Regression #5 – High NE Group for Round-one opinion Regress Round_1_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue .24 .34 0.71 0.48 Ognowski Cue -.24 .36 -0.65 0.51 Issue Frame .68 .35 1.95 0.05* Image Frame -.20 .35 -0.59 0.55 Constant 3.77 .31 12.23 0.00 N = 199 R2 = .045 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

My first hypothesis, looking at the difference in frame and cue effects for low vs.

high NE individuals after the initial exposure, appears to neither be confirmed nor

rejected. Regression #1 showed a significant effect of both of the frames and neither of

the cues when looking at all respondents. Regressions #4 and #5, however, show that for

low NE individuals the image frame was significant, and for high NE individuals the

issue frame was significant – and the cues were significant for neither. Why this

difference in frame effect appears is unclear, although it is shown through regressions #4

and #5 that the effect of cues for low and high NE individuals seem to be consistent for

round-one (in both cases all the cues are insignificant). One possibility is that high NE

individuals may be more motivated to focus on issues than are low NE individuals.

An equivalent regression can be estimated for low NE and high NE on round-two

opinion, and is shown below in regression #6 and #7. The low NE group shows

significance for both cues on round-two opinion, but neither frame shows significance on

round-two decision making for low NE individuals. The high NE group shows

significance for both frames, but not for either of the cues. These results indicate strong

evidence that the two groups are forming opinions differently in round-two. It is

29

particularly interesting to see the emergence of cues as so significant for the low on-line

NE group. The reasoning, and true significance, of this is discussed further below.

Regression #6 – Low NE Group for Round-two opinion Regress Round_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue 1.56 .30 5.21 0.00*** Ognowski Cue -1.22 .29 -4.23 0.00*** Issue Frame .10 .29 0.34 0.73 Image Frame -.23 .29 -0.80 0.43 Constant 3.81 .27 14.36 0.00 N = 183 R2 = .351 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

Regression #7 – High NE Group for Round-two opinion Regress Round_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Variables Coef. Std. Error T P>|t| Tierney Cue .39 .35 1.11 0.27 Ognowski Cue .06 .38 .15 0.88 Issue Frame .69 .36 1.96 0.05* Image Frame -.71 .36 -1.94 0.05* Constant 3.70 .32 11.30 0.00 N = 172 R2 = .090 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

As done in the General Analysis section above, next we complete a regression by

adding in the round-two vote as an independent variable, in an attempt to isolate the true

affect of the frames and cues on respondents’ round-two decision – taking out the affect

the stimuli already had on the individuals’ round-one opinion. To recount the result of

regression #3 above, adding in round-one vote rendered the frames insignificant, with the

cues still being significant. This pattern is continued in the following two regressions,

which do the equivalent regression except split by NE group. Regression #8 shows that

round-one vote is highly significant for the low NE group, as are both of the cues.

Regression #9, however, shows the only significant variable is round-one vote (although

the image frame is very marginally significant).

30

Regression #8 – Low NE Group for Round-two opinion Regress Rd_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Rd.1 Vote Variables Coef. Std. Error T P>|t| Tierney Cue 1.48 .28 5.27 0.00*** Ognowski Cue -1.14 .27 -4.23 0.00*** Issue Frame .07 .27 0.27 0.78 Image Frame -.07 .27 -0.26 0.80 Rd. 1 Vote 0.29 .06 5.02 0.00*** Constant 2.63 .34 7.65 0.00 N = 183 R2 = .433 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

Regression #9 – High NE Group for Round-two opinion Regress Rd_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Rd.1 Vote Variables Coef. Std. Error T P>|t| Tierney Cue .09 .26 0.37 0.71 Ognowski Cue .10 .27 0.36 0.72 Issue Frame .29 .26 1.11 0.27 Image Frame -.37 .27 -1.38 0.17 Rd. 1 Vote 0.68 .05 12.45 0.00*** Constant 1.16 .31 3.70 0.00 N = 172 R2 = .530 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

Regressions #8 and #9 indicate that low NE individuals during round-two are

trying to reconstruct their opinions, which is consistent since low NE individuals

presumably do not have running evaluations from which to draw. They will have some

memory of their round-one decision, but will supplement that by recalling the

endorsement cues, which they were presented with during the initial study. The cues

probably have more of an impact during round-two than they did during round-one

because they are much simpler to remember as compared with frames. Which candidate

was endorsed is much more direct than remembering a frame, which suggests that

individuals decide based on a particular quality, and then the qualities of the candidates

as related to the frame. Most interesting, however, is that instead of fading in importance

and impact, the cue stimuli seem to increase their impact over time. Regression #8

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supported hypothesis #3, that cues more significantly impact round-two decisions for low

NE individuals than do frames.

In comparison, members of the high NE group were able to pull up their running

opinion already generated (i.e. their round-one vote) and base their decision almost solely

on this as opposed to thinking back to the frames, cues, and information presented in

round-one of the study.

The last regression presented, regression #10, adds in a dummy variable for NE

along with interaction terms of the NE dummy and other independent variables (each of

the four stimuli as well as round-one decision). This regression is constructed to check

the statistical significance of the dynamic discussed above that low on-line individuals

(low NE) were more significantly impacted by cues in round-two than their high NE

counterparts. In the regression, high NE individuals are scored as 1 for the dummy

variable, with low NE respondents scored 0.

Of note in the results are three significant variables: the interaction variables of

round-one vote, Tierney cue, and Ognowski cue. The positive significant effect of the

interaction round-one vote variable indicates that a respondent’s round-one vote was

much more significant for high NE individuals as compared with low NE individuals.

The negative and significant Tierney cue interaction, as well as the positive and

significant Ognowski interaction variable, indicate that the impact of cues on round-two

decision making is much stronger for low NE respondents. This is shown because the

interaction cue variables push in the opposite direction to how the variables normally

work (i.e. the Tierney cue pushes individuals towards Ognowski, and the Ognowski cue

pushes individuals towards Tierney). This result is essentially making up for the even

32

stronger effect the normal two cues variables have in the regression – meaning it is

minimizing the cue-effect for the high NE respondents. Thus, our observation is

confirmed through statistical significance in this last regression.

Regression #10 – Both NE Groups for Round-two opinion Regress Rd_2_Vote on Tierney_Cue Ognowski_Cue Issue_Frame Image_Frame Rd.1 Vote NE_Dummy NE_Rd.1_Vote NE_Issue NE_Image NE_Tierney_Cue NE_Ognowski_Cue Variables Coef. Std. Error T P>|t| Tierney Cue 1.47 .28 5.31 0.00*** Ognowski Cue -1.15 .27 -4.36 0.00*** Issue Frame .08 .26 0.31 0.76 Image Frame -.02 .27 -0.08 0.94 Rd. 1 Vote .36 .05 6.78 0.00*** NE Dummy -1.03 .46 -2.31 .02** NE Rd. 1 Vote .27 .07 3.81 .00*** NE Issue .25 .38 0.68 .50 NE Image -.35 .39 -0.89 .37 NE Tierney Cue -1.32 .38 -3.42 .00*** NE Ognowski Cue 1.29 .39 3.28 .00*** Constant 2.36 .32 7.29 .00 N = 355 R2 = .469 * = sig. at 90%, ** = sig, at 95%, *** = sig. at 99%

Regression #10 provides support for hypothesis #2, namely that individuals with

high NE are more likely to be consistent on candidate preference over time. The

hypothesis is supported because the interaction variable of NE score and round-one

opinion is significant. That is, the fact that the interaction variable is positively significant

shows evidence that there is an additional effect of the round-one opinion for high NE

respondents as compared with low NE respondents.

Finally, we present several graphical depictions of the impact of cue effects and

frame effects over time for the two different NE groups. The charts and corresponding

graphs look at the change in average score for exposure to either the Tierney cue or the

Ognowski cue. In other words, we ignore the control group for these charts, and take the

% difference from the 1-7 scale between those individuals exposed to the Tierney cue

33

against those exposed to the Ognowski cue. The first chart shows that for the low NE

group (the line with the square on the end), cues seem to have an enormous impact over

time, whereas not nearly as much for high NE individuals.

CUE EFFECT Time 1 Time 2 All 9.17% 28.00% Low NE 11.00% 46.33% High NE 8.00% 5.33%

The frame effect chart and graph below do an equivalent analysis, except this time

comparing percentage difference over time for individuals having an issue frame against

those with an image frame in round-one (again ignoring control groups). The results

show much smaller changes, but particularly of note is that for high NE individuals, the

frames maintain their effect over-time, whereas the effect fades for the low NE line.

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Frame EFFECT Time 1 Time 2 All 14.50% 12.50% Low NE 14.00% 5.17% High NE 15.00% 20.83%

35

IX. Conclusion

The results of our study help advance the field of political framing and the

political science understanding of the effect of time on the influence of both cues and

frames. Prior to our study, it had not been analyzed what difference of effect cues would

have over time for individuals varying in on-line processing characteristics. Most

interesting in our results is effect of the cues observed – instead of the impact of the cues

decreasing over time, their importance appears to increase over time for individuals with

a low NE. This goes against the idea that frames and cues are short-lived, that is that

their importance and influence decreases over time.

A possible explanation for this phenomenon is that when presented with large

amounts of information individuals are able to synthesize and create opinion mostly on

their own, but later on when not being able to remember the intricacies of a situation or

campaign individuals resort to remembering who a political elite endorsed. Thus, while

endorsements (political cues) are not necessarily the most influential indicator in opinion

formation immediately after expanded exposure to an issue or campaign, their importance

grows as one’s familiarity with the issue or campaign decreases over time. Our study

advanced the field of political framing by completing a study over time which looked at

both cues and frames, and how they interact, instead of solely cues or solely frames.

There are several areas in which we would like to extend our study and work. Of

particular interest to me would be to complete a similar study with more time points. So,

instead of only having one follow-up questionnaire two weeks after the initial exposure to

the information, cues and frames, we would have two or more follow-up questionnaires.

This would make it possible to do time-series regressions to observe how the effects of

36

the different cues and frames change over particular amounts of times, rather than how

they change over “time” in a general sense. In other words, it would be interesting to

observe if the effects of “time” took an hour, day, or week to begin to take effect and be

observable.

It would also be interesting to complete a study of frames and cues by presenting

stimuli to respondents at different points of time. For our study, we solely presented

stimuli in round-one – round-two was only completion of a questionnaire – but it would

be interesting to see what effect additional exposure to stimuli would have on the impact

of frames and cues from previous time periods. In a real-life competitive campaign

situation, there would be multiple exposures to frames and cues over time, not solely one

exposure followed by a waiting time prior to the election day or decision making

moment. Thus, our results look at what the effect of the initial frames and cues would be

if there were no other contacts made – something unrealistic for a real-life situation. Our

study does, however, provide a launching point to these two more advanced study ideas.

Overall, our study more closely replicates the complexities and intricacies of real-

life competitive situations, while maintaining the simplicity to be able to analyze results

in a significant manner. Our results indicate that individual candidates and political

parties should focus on providing argumentation leading to high NE individuals quickly

making evaluative decisions early in a campaign, as well as on cues and arguments that

are easily remembered for low NE individuals to remember and process on or near the

election or decision making time.

37

Appendix #1 – T-Tests for Low NE vs High NE Vote-Choice

Test #1 – for Round-one Two-sample t test with equal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- Low NE | 212 3.853774 .133604 1.945303 3.590404 4.117143 High NE | 199 3.949749 .143864 2.029452 3.666046 4.233451 ---------+-------------------------------------------------------------------- combined | 411 3.900243 .0978952 1.984642 3.707804 4.092682 ---------+-------------------------------------------------------------------- diff | -.0959752 .1960703 -.4814064 .2894561 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.4895 Ho: diff = 0 degrees of freedom = 409 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.3124 Pr(|T| > |t|) = 0.6248 Pr(T > t) = 0.6876 **For all three hypotheses, the null hypothesis that the means are equal can not be rejected. Test #2 – for Round-two Two-sample t test with equal variances ------------------------------------------------------------------------------ Group | Obs Mean Std. Err. Std. Dev. [95% Conf. Interval] ---------+-------------------------------------------------------------------- Low NE | 183 3.803279 .144446 1.954029 3.518275 4.088283 High NE | 172 3.901163 .1533124 2.010673 3.598534 4.203791 ---------+-------------------------------------------------------------------- combined | 355 3.850704 .1050597 1.979476 3.644085 4.057324 ---------+-------------------------------------------------------------------- diff | -.0978841 .2104534 -.5117843 .3160161 ------------------------------------------------------------------------------ diff = mean(0) - mean(1) t = -0.4651 Ho: diff = 0 degrees of freedom = 353 Ha: diff < 0 Ha: diff != 0 Ha: diff > 0 Pr(T < t) = 0.3211 Pr(|T| > |t|) = 0.6421 Pr(T > t) = 0.6789

**For all three hypotheses, the null hypothesis that the means are equal can not be rejected.

38

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