understanding the influence of others on perceptions of a message's advocacy: testing a...

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Understanding the Influence ofOthers on Perceptions of a Message'sAdvocacy: Testing a Two-Step ModelRachel A. Smith & Franklin J. BosterPublished online: 11 Aug 2009.

To cite this article: Rachel A. Smith & Franklin J. Boster (2009) Understanding the Influenceof Others on Perceptions of a Message's Advocacy: Testing a Two-Step Model, CommunicationMonographs, 76:3, 333-350

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Understanding the Influence of Otherson Perceptions of a Message’sAdvocacy: Testing a Two-Step ModelRachel A. Smith & Franklin J. Boster

Asch proposed that contextual information changes how people interpret objects under

evaluation. This paper extended his insight by merging range�frequency theory and the

linear discrepancy model into a two-step model of social influence. In the first step,

people interpret a message’s advocated position differently with knowledge of how other

people interpreted the message than without this knowledge. In the second step, peoples’

interpretations influence how their attitudes change toward the message’s recommenda-

tions. A two-step model was proposed: (a) knowing what bias other people thought a

newspaper article presents affected how participants perceive the extremity of this article’s

advocated position, and (b) participants’ interpretations influenced how they changed

their attitudes toward the article’s topic. The results from this first experiment were

consistent with the two-step model. A second experiment shows that the degree of

ambiguity in a message can increase or inhibit this effect. Together, these studies provide

insight into how public opinions may serve as contextual influences on people’s

perceptions of the issues at hand and their responses to them.

Keywords: Social influence; Norms; Interpretation; Persuasion

Scientific controversies constantly resolve themselves into differences about the

meaning of words.

*A. Schuster (as quoted in Ogden & Richards, 1923, p. vi)

People may have heard about a message from others before they have a chance to

process it for themselves. For example, someone may overhear colleagues talking

Rachel A. Smith (PhD, Michigan State University) is an Assistant Professor in the Department of

Communication Arts & Sciences at The Pennsylvania State University. Franklin J. Boster (PhD, Michigan

State University) is a Professor in the Department of Communication at Michigan State University. This research

was developed from the first author’s dissertation under the advisorship of the second author. The authors

would like to thank Dr. Allen and the anonymous reviewers for their helpful feedback. Correspondence to:

Rachel Smith, Department of Communication Arts & Sciences, The Pennsylvania State University, 318 Sparks

Bldg, University Park, PA 16802, USA. E-mail: [email protected]

ISSN 0363-7751 (print)/ISSN 1479-5787 (online) # 2009 National Communication Association

DOI: 10.1080/03637750903074719

Communication Monographs

Vol. 76, No. 3, September 2009, pp. 333�350

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about a newspaper article, before having a chance to read it. After hearing others give

their own perceptions of the article, people may perceive it differently than if they

previously had not heard anyone else’s thoughts. For example, they may perceive the

article as more or less biased in its coverage of the issue it addresses. Asch (1940)

proposed that this social influence, or change of judgment in response to group

standards, was due to ‘‘a change in the object of judgment, rather than in the judgment

of the object’’ (p. 455, italics in the original). Asch (1940, 1948) provided insight that

guided a different theoretical explanation for social influence; however, he never

articulated a process by which this type of social influence may occur.

If contextual features alter people’s perception of a message’s advocated position,

then persuasion theories that depend on the discrepancy between a person’s position

and a message’s position on some issue will be impacted. Such theories include the

information processing model (e.g., Boster, Mayer, Hunter, & Hale, 1980; French,

1956), information integration theory (e.g., Anderson, 1981), and social judgment

theory (e.g., Sherif & Hovland, 1961). This paper expands on how knowledge of

others’ interpretations may change how people interpret messages, and subsequently

change their attitudes. Specifically, this paper investigates the following two-step

model: (a) that knowledge of others’ interpretations serves as a contextual feature

that affects how people perceive the extremity of a message’s advocated position

toward some issue, and in turn, (b) people change their attitudes toward their

message perceptions. The next several paragraphs review work on content and

context as well as the two theories pivotal to this merger: range�frequency theory

(Parducci, 1965, 1995; Volkmann, 1951) and the linear discrepancy model (Hunter,

Levine, & Sayers, 1976).

Content and Context

Many English words can refer to more than one concept, and contextual information

often guides how people disambiguate their meaning (Rodd, Gaskell, & Marslen-

Wilson, 2000) as well as the message in which they occur. Since the 1940s, scholars

have investigated the role of context in determining a message’s meaning. They

investigated syntactical matters, including word agreement (e.g., Gollob, 1968, 1974;

Heise, 1969), character balance (Leaf, Kanouse, Jones, & Abelson, 1968; Lerner &

Simmons, 1966), and question wording (see Kahneman, Slovic, & Tversky, 1982 for a

review), as well as sociolinguistic (Armstrong & Kaplowitz, 2001) and relational

information (Gerbing & Hunter, 1979). For example, social pressures and motiva-

tional goals, such as rejecting a strongly disliked group identity (Wood, 2000) or

engaging a sense of rivalry (Smith & Boster, 2002), emphasize the importance and

relevance of particular consequences or attributes over others. Rating scales and labels

provide contextual cues that influence reports of attitudes and behavior (e.g.,

Converse & Presser, 1986; Sudman, Bradburn, & Schwarz, 1996; Tourangeau, 1999;

Tourangeau, Rips, & Rasinski, 2000), as they provide norms or standards to which

people can compare themselves (Schwarz, Hippler, Deutsch, & Strack, 1985).

334 R. A. Smith & F. J. Boster

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Previous scholars have found that varying a message’s source (Lorge, 1936) or

asking participants to think about more or less militant people (Burgoon, 1970)

influenced people’s interpretations of a message’s advocated position. Allen and

Wilder (1980) found that knowing other people’s perceptions of ambiguous phrases

(e.g., ‘‘go out of my way’’ p. 1118) influenced their participants’ interpretations of

these phrases (from ‘‘be inconvenienced’’ to ‘‘risk my life’’). They found that

knowledge of others’ interpretations influenced participants’ own interpretations in

ways that could not be explained by simple conformity to a group norm. Further,

they found that participants’ interpretations affected the extent to which participants

agreed or disagreed with the entire sentence in which the phrase appeared.

Wood (2000) argued that scholars must clarify the interplay of content and context

in message interpretation and social influence. To understand perception, one may

turn to theories in psychophysics such as range�frequency theory (Parducci, 1965,

1995; Volkmann, 1951).

Range�Frequency Theory

Range�frequency theory (Parducci, 1965, 1995; Volkmann, 1951) posits that a target’s

location within a distribution of salient, contextual stimuli determines its judged

value. Extending this idea to message interpretation, the perception of a message’s

advocated position relies on its location within a salient distribution of others’

interpretations of it. For example, readers’ memory of how others interpreted a

newspaper article’s advocated position on an issue would impact readers’ own

perceptions of biased coverage when they read it.

Range�frequency theory argues for the important of two estimated values. The

range value (Parducci, 1965; Volkmann, 1951) is an estimate of the relative

discrepancy, in this case, between the message’s content and the two end-points of

a subjective interpretation scale. Others’ interpretations would set the end-points of a

subjective scale on which a person interprets the message. If someone heard a range of

interpretations from positive to neutral, then these two positions would set the end-

points. If another person heard a range of interpretations from neutral to very

negative, then the end-points of the subjective interpretation scale for this person

would be very different (neutral to very negative) from the first person (positive to

neutral).

All other things being equal, the range value increases as the distance between the

message content and each end-point of the subjective scale becomes more unequal. If

a message’s content is closer to a positive end-point than a negative end-point, then

the range value will increase positively. If a message’s content is asymmetrically closer

to a negative end-point, then range value will increase negatively. The range value,

Rmc, of Message m in Context c is given as

Rmc � (Sm�Sf )= j Smax�Smin j;where Sm is the extremity of a message’s advocated position, Smin and Smax are the

minimum and maximum interpretations that others provided, and Sf is the observed

maximum or minimum that is farthest from the message. In cases where the message

Ambiguity and Persuasion 335

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advocates against an issue, the numerator changes; the message is subtracted from the

farthest point.

The frequency value (Parducci, 1965) is an estimate of the location of the target

stimulus described by its rank within a set of stimuli. The frequency affects the

subjective interpretation scale in the following way: People provide each interpreta-

tion equal space on their subjective scales (Parducci, 1995; Volkmann, 1951). If

people hear three interpretations of a positive bias, then they provide each positive

interpretation equivalent mental space on their subjective advocacy scale. In order to

provide equal space mentally the positive end-point stretches to accommodate each

of the three positive interpretations. With each additional positive interpretation, the

positive end-point expands. As this expansion on the positive end continues a reader

may perceive the other end-point (be it neutral or negative) as subjectively closer, and

therefore representative of the message’s content, than the outstretched, positive end-

point.

Holding all else constant, the frequency value increases as the number of others’

interpretations falling on either side of the message content becomes less

symmetrical. If others provide more negative than positive interpretations of a

message, relative to the message’s content, the frequency value will increase positively.

In the opposite case the frequency value will increase negatively. The frequency value,

Fmc, of Message m in Context c is given as

Fmc � (nn�np)=(Nc �1);

where nn is the number of interpretations that are more negative than the message

and np is the number of interpretations that are more positive than the message. Nc is

the total number of others’ interpretations of the message. Others’ interpretations

that match the message’s content are counted with the interpretations between the

message and the farther end-point.

Interpretations of messages are influenced by the weighted, linear combination of

both range and frequency values. As the range value becomes increasingly negative a

reader will form a more negative interpretation of a message, because this reader

interprets this message’s content as more representative of the closer, negative end-

point of the subjective scale. As the frequency value becomes increasingly negative, a

reader will interpret a message as more negative. Without reason to anticipate that

one value is more critical to perception than another, the range and frequency values

are summed to form a total predicted social influence on people’s interpretation of

the extremity of a message’s advocated position.

To illustrate the predictions, Figure 1 shows a sample of others’ interpretations of a

newspaper article’s advocated position (marked with Xs). The distribution ranges on

a scale from �5 to �5. In the first situation, students either read the message that is

rated in the most context-free possible situation as �2 (moderately against an issue,

M1 in the figure) or as 2 (moderately in favor of this issue, M2 in the figure) on the

same scale. The moderately unfavorable message (M1) within this distribution of

interpretations has a range value of �.7 [i.e., (�2� 5)/j(�5)�5j] and a frequency

value of �.7 [i.e., (2�9)/(11�1)], combining to a �1.4 influence, leading to a


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more unfavorable interpretation of the issue than a context free interpretation. The

moderately favorable message (M2) within the same distribution has a range value of

.7 [i.e., (2�(�5))/j5�(�5)j] and a frequency value of .3 [i.e., (7�4)/(11�1)],

combining to a 1.0 influence, leading to a more favorable interpretation of the issue

than a context free interpretation. When comparing the relative influences on the

favorable and unfavorable message, the discrepancy between the message interpreta-

tions and the context-free interpretation is expected to be higher for the unfavorable

message than the favorable message.

This study examines if pre-existing knowledge of how much bias others believe a

newspaper article portrays toward the issue, estimated from a combination of range

and frequency estimates, alters participants’ own perceptions of this article’s

advocacy. The following hypothesis is proposed:

H1: The predicted social influence score, derived from the combination of range and

frequency values, will correlate positively with participants’ discrepant assessment,

from a control group, of a newspaper article’s advocacy.

Linear Discrepancy Model of Attitude Change

The second step of the proposed model uses the linear discrepancy model (Hunter

et al., 1976) to predict attitude change. After people interpret a message, they

compare this message’s advocated position to their present attitude. Holding all else

constant, attitude change is a function of how much discrepancy exists between the

position advocated in the message and the recipient’s position (e.g., French, 1956;

Hunter et al., 1976). As this discrepancy increases, attitudes change proportionally

toward the message’s advocated position (e.g., French, 1956; Hunter et al., 1976). This

model is consistent with data obtained in many attitude and opinion change

experiments (e.g., Danes, Hunter, & Woelfel, 1978; Hovland & Pritzker, 1957) and

group decisions (e.g., Boster, Fryrear, Mongeau, & Hunter, 1982; Boster, Hunter, &

Hale, 1991; Boster et al., 1980). The following hypothesis is proposed:

H2: Participants will change their attitudes about an issue toward the position they

believe the newspaper article holds about this issue.

X X X X X X X X X X X

-5 -4 -3 -2 -1 0 1 2 3 4 5

Against the Issue Supporting the Issue

M1 M2

Figure 1 Distribution of others’ interpretations (each one is designated by an ‘‘X’’) of

two articles’ advocated positions for or against new campus parking plan. The two arrows

represent the two articles’ advocated positions when their respective content is evaluated

in the most objective or context-free of circumstances.


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Experiment 1

Participants

Undergraduate students (n�276) enrolled in communication courses at a large

Midwest university participated in this study. On average, participants were 21 years

old (SD�1.63) and in their third year at the college (SD�0.89). More women

participated (71 percent of participants) than men.

Design

The experimental design was a scope (wide or narrow) by distribution (negative-skew

or symmetrical) by message topic (new campus parking plan, major prerequisite, or

teaching assistants) factorial design with approximately 20 participants per condition

(n�240). Variation in the scope and distribution of other (fictitious) students’

interpretations of an article induced differences in participants’ range and frequency

values. Participants completed an attitude survey before and after reading other

students opinions about one of three possible newspaper articles and the article itself.

The articles covered three possible topics: a new campus parking plan, a required

statistical course for communication majors, and international graduate teaching

assistants in undergraduate education. These messages are available upon request. A

control group of participants (n�36) only read one of the three articles (about 13

participants per article) and did not read the other (fictitious) students’ opinions.

Procedure

The experimenter told participants they would be helping to develop stimulus

materials for a future study. These materials were newspaper articles from the

students’ local newspaper. The students were led to believe that the experimenter

needed to know if these articles presented balanced, objective, neutral coverage of an

issue before using them in a future experiment. First, participants completed a short

questionnaire in order to find out their pre-existing opinions on issues including: (a)

a new campus parking plan to establish perimeter parking around campus and rely

on quick mass transit rather than front-door parking, (b) new course requirement

(taking a statistics class) before declaring a major, and (c) the use of international

teaching assistants in undergraduate education. These three topics represent the

issues covered in the three stimulus articles. (Most participants, 70 percent, reported

majoring in communication and most, 80 percent, reported driving a car on campus.

This suggests that the issues hold relevance for this audience.)

After completing the questionnaire participants were given a second packet. First,

they read how to categorize and to scale others’ interpretations of one newspaper

article. Many studies have investigated how contextual features determine the

perceived level of discrepancy between a message and its reader (see Kaplowitz &

Fink, 1997 for a review). In order to control for these issues, as well as ingroup�outgroup source effects, these 10 sources were described simply as other university

students. Participants were told ‘‘In an earlier study, we asked 10 other students to

read a section of a newspaper article. Each of the 10 students wrote down what they


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thought the article was advocating, in other words, they wrote down if they

interpreted the article as favorable, unfavorable, or neutral toward an issue.’’ The

experimenter explained that these other (fictitious) students did not write down if

they personally liked the article or the topic, but they wrote down to what degree they

felt that the newspaper article presented biased coverage.

The participants read 10 interpretations of the newspaper article, and then

followed the instructions on how to construct a scale to arrange these interpretations.

They constructed a scale by marking freehand where they thought each of the 10

interpretations fell using a preprinted line on the survey. Figure 1 shows how a

participant might have marked the opinions they read with Xs. For publishing

purposes, the figure shows Xs in different locations within the same vertical plane,

but participants could, and often did, mark more than one of the 10 responses in the

same place or in a vertical line. After they finished arranging the other (fictitious)

students’ interpretations along the line, participants identified the most extreme

interpretations (i.e., the ones furthest to the left and furthest to the right). After

identifying these extremes participants wrote down a label underneath these extremes

from a list of words including ‘‘neutral, opposed, or favorable’’ and the qualifiers

‘‘very, moderately, or mildly.’’ Consequently, some participants produced scales

anchored with ‘‘very opposed’’ to ‘‘very neutral;’’ other scales were anchored by

‘‘mildly favorable’’ to ‘‘very opposed.’’

After arranging the others’ interpretations on their constructed scale, participants

assessed the 10 interpretations on standardized, likert-type scales: three scales for each

interpretation. Participants, then, provided their opinion of the other students’

credibility. Afterwards, participants read the newspaper article, supposedly read by

the other 10 students previously. Participants provided their own perception of how

the article covered the issue, and wrote down who they believed authored the article.

Last, participants completed the pre-exposure attitude scales a second time.

Those participants in the control group heard that they were to evaluate articles

from their local university newspaper. This condition differed from the experiment,

in that these participants heard no information about others reading the article

beforehand.

Instrumentation

The indicators (i.e., measures) used in all experiments were tested for unidimension-

ality (Hunter & Gerbing, 1982). For the measurement model, the following cutoffs

were used: CFI �.90, RMSEA�.08, SRMR�.09; these are considered acceptable for

sample sizes below 250 (Holbert & Stephenson, 2002). Measurement model including

article advocacy, attitude toward topics, and others’ credibility was estimated with

maximum likelihood. The model passed goodness-of-fit criteria, CFI �.96,

RMSEA�.06 [90 percent CI, .05�.07], SRMR�.05, with x2 (df�398,

N�240)�684.79, pB.001.

Article advocacy. Participants indicated their interpretations of an article’s advocacy

of an issue with (a) an open-ended question, asking them how they interpreted the

newspaper article’s meaning and (b) three semantic differential items with 9-point


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response scales. Items asked participants to rate the extremity of their article’s

advocated position (a new campus parking plan, the new course requirement, or

international teaching assistants) with anchors, very favorable�very unfavorable,

strongly like�strongly dislike, and strongly support�strongly oppose. The advocacy

measures were reliable: new campus parking plan, Cronbach’s a�.97, major

prerequisite, Cronbach’s a�.95, and international teaching assistants, Cronbach’s

a�.96. A single summed score for article advocacy was generated, 12�strongly

supported, �12�strongly opposed.

Attitude toward topic. Participants indicated their attitudes toward issues covered in

their local paper on three semantic differential items with nine-point response scales

for each issue. Items asked participants how they felt about an issue, such as the new

campus parking plan, with anchors, very favorable�very unfavorable, strongly like�strongly dislike, and strongly support�strongly oppose. A single summed score for each

issue was generated at each time period, 12�strongly supported, �12�strongly

opposed. Table 1 presents reliabilities, means, and standard deviations for these

measures.

Range and frequency values. Participants scaled what bias others (fictitious and

labeled with letters ‘‘a’’ through ‘‘j’’ to retain anonymity) thought an article exhibited

on three semantic differential items with nine-point response scales anchored by very

favorable�very unfavorable, strongly like�strongly dislike, and strongly support�strongly

oppose. A single summed score for each person was generated, 12�strongly supported,

�12�strongly opposed, Cronbach’s a�.99.

To induce different range and frequency values, the scope of each distribution was

varied. The narrow condition provided interpretations four points above and below

the message’s content; the wide condition spanned seven points above and below the

message’s content. For the symmetrical distribution an equal number of opinions

were more positive and negative than the message for the negatively skewed

distribution, seven opinions were more positive and three opinions were more

negative than the content. Table 2 provides descriptive statistics for participants’

estimates of other students’ interpretations by experimental condition. These data did

not vary by article topic (FB1).

The maximum and minimum scores each participant gave for the others’

interpretations were used to calculate a range value denominator. The absolute

Table 1 Summary of Reliabilities, Scale Means, and Standard Deviations in Experiment 1

Time 1 Time 2 Change

Variable a M SD a M SD a M SD

New campus parking plan .98 �1.43 4.87 .99 �4.58 5.39 .95 �2.46 5.61Statistical course

requirement.98 0.58 4.72 .98 0.35 5.03 .92 0.04 3.08

International teachingassistants

.97 �1.83 4.91 .97 �0.28 5.78 .95 1.36 4.94


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difference between the extreme interpretations from others served as the range value

denominator. The range value numerator was calculated by (a) determining which

interpretation from the others resided the farthest from the control group’s estimate,

and then (b) subtracting this interpretation from it. The range value then is the

proportion of asymmetrical distance over absolute range.

For their frequency value numerator the experimenter counted the number of

others’ interpretations scaled more positively and negatively than baseline estimates.

The number of others evaluated, 10, served for their frequency value denominator.

The two values were summed into a single predicted social influence score.

Descriptive statistics of range value and frequency values may be seen in Table 2.

Others’ credibility. Participants indicated the credibility of each of the others

(fictitious) who interpreted their newspaper article on a single item with a 5-point

response scale, 5�very credible, 1�very uncredible. These 10 scores, one for each

fictitious student, were rescaled, 2�very credible, �2�very uncredible. The

reliability of this estimate was modest, Cronbach’s a�.65.

Analysis

After providing descriptive statistics, we used a path analysis to test the two-step

model. Correlations were used to test how well the data fit the linear discrepancy

model.

Results

Participants in the control group read one of the three articles without learning of

anyone else’s opinion beforehand. Participants reported that the newspaper articles

presented a negative bias about the issues (M��5.45, SD�5.24). Although the

negative bias did not differ substantially across article topics, F (2, 34)�2.06, ns, the

article against adopting the new campus parking plan (M��2.90, SD�7.10) was

rated as less negative than the article against requiring a statistical course before

Table 2 Means and Standard Deviation of Others’ Interpretations by Experimental

Conditions

Narrow Wide

Normal Negative skew Normal Negative skew

Max �4.05 1.97 �3.92 0.86Min �7.83 �8.02 �9.61 �9.89Number positive 5 7 5 7Number negative 5 3 5 3Range �0.52 (0.64) �0.63 (0.63) �0.46 (0.26) �0.82 (0.72)Frequency �.11 (0.44) �0.46 (0.56) �0.18 (0.37) �0.64 (0.33)Social influence

prediction�0.63 (0.99) �1.09 (1.21) �0.64 (0.58) �1.46 (0.76)

Note. This message’s content was rated on a scale ranging from 12�strongly supported to �12�strongly opposed.


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declaring a communication major (M��6.00, SD�5.16) or against employing

international teaching assistants in undergraduate classes (M��7.72, SD�5.60).

Experimental participants rated these fictitious students, who presumably read the

article beforehand and provided their bias assessments, as credible (M�.94, SD�1.38). Perceived credibility did not differ statistically by experimental conditions or

articles’ topics. When asked, participants most often guessed that the article was

written by a peer (77 percent), followed by a university administrator (18 percent) or

a nonstudent newspaper reporter (5 percent).

Article Interpretation

The social influence hypothesis coincided with these data (see Figure 2). Their social

influence score, the sum of frequency and range values developed from each

participant’s exposure to (fictitious) others’ interpretations of their article, accounted

for how participants’ interpretations deviated from the control groups’ interpreta-

tions, r(238)�.31, pB.05. Experimental conditions, articles’ topics, and assessments

of fictitious students’ credibility had no substantial impact on article interpretation.

Attitude Change

After reading a newspaper article, all participants’ attitudes toward the issue in their

article, including those in the control group, became less favorable (M change��1.82, SD�5.37), statistically lower than zero change, one-sample t(238)��4.82,

pB.05. As experimental participants thought the article presented a more negative

bias than the control group, their attitudes toward the topic also changed in a

negative direction, r(238)�.27, pB.05. The linear discrepancy model (Hunter et al.,

1976) fit these data well. As predicted by the model the correlation between

participants’ initial attitude toward the topic and their attitude change was negative,

r(237)��.41 and the autocorrelation between the initial and final attitude reports

was strong, r(237)�.49.

This two-step model was consistent with the data. Others’ interpretations

influenced how participants interpreted an article and participants’ interpretations,

in turn, influenced how they changed their attitudes toward new campus parking

plan. A causal model was estimated with the method of ordinary least squares,

without allowing errors to covary (see Table 3 for zero-order correlations among

.27*Computed

social influence Influenced articleinterpretation

Attitudechange

.31*

χ2 (1,237) = .01, ns, RMSE = .00

Figure 2 Computed social influence score, a combination of range and frequency values,

influencing how participants’ interpretations of the newspaper article’s bias toward the

article’s issue deviated from the control group. The participants’ deviations from the

control group predict how their attitudes changed toward the article’s issue. Uncorrected

parameter estimates and goodness-of-fit indices from experiment 1 are presented.


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variables). Both uncorrected parameter estimates were statically significant and the

global test of the model indicated an accurate fit, x2 (1, N�240)�.01, ns. A

commonly employed measure of fit, the root mean squared error, was very small,

RMSE�.00. Thus, the two-step model coincides with these data (see Figure 3 for the

model with uncorrected, parameter estimates).

Discussion

This experiment found data consistent with a two-step model of social influence,

which was inspired by Asch’s (1940) conclusion that group standards change how

people interpret objects under evaluation. These findings support the prediction that

pre-existing knowledge of other peoples’ thoughts about a newspaper article’s bias,

estimated with range and frequency values, affects readers’ subsequent perceptions of

an article’s bias. This perception, in turn, predicted how readers’ attitudes changed.

The small direct relationship between the social influence score and observed attitude

change coincides with the prediction that this is a mediated process. One also may

note that the topics had little impact on the model. Observing consistency across

multiple topics suggests that the model is robust across issues.

This model presumes that a message must have some level of ambiguity in order to

require the use of contextual information, such as what others’ perceptions of a

message. Put differently, social influence increases as ambiguity increases (Crutchfield,

1955; Sherif, 1935; West, 1981). The exceptions to this general rule appear when

participants made preference judgments (e.g., food preferences). Social influence was

minimal with such judgments, because people do not need others to determine how to

interpret their own preferences (Crutchfield, 1955). Without ambiguity, contextual

effects on perception is attenuated.

This second study tests the fundamental assumption that the strength of the

predicted social influence on message interpretations varies as the ambiguity of the

words used within a newspaper article varies. To test this fundamental assumption

the second experiment replaces words in one experimental article with synonyms that

possess more or less semantic ambiguity. Semantic ambiguity (Rodd et al., 2000)

describes words that can refer to more than one concept. To understand such words,

people need to select one of the concepts, and this selection is often biased by the

context in which the word occurs (Rodd et al., 2000). Studies of semantic ambiguity

typically test speed and errors in recognizing real words versus nonword stimuli (e.g.,

Table 3 Correlations Among Variables in Experiment 1

M SD a 1. 2. 3.

1. Predicted social influence �0.96 1.15 NA �2. Message interpretation �5.45 5.24 .96 .31 �3. Attitude change �1.82 5.37 .94 .07 .27 �4. Others’ credibility 0.94 1.38 .65 .08 .07 .08


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Rodd et al., 2000); to date, the relationship between semantic ambiguity and

perceptions of message advocacy has not been tested. The following hypothesis is

proposed:

H3: The relationship between the predicted social influence score and participants’

assessment of the message’s advocacy will increase when reading a newspaper

article containing more ambiguous versus less ambiguous words.

Experiment 2: Method

Participants

Undergraduate students (n�40) enrolled in communication courses at a large

Midwestern university participated in this study. Participants were 22 years old

(SD�.85), primarily in their fourth year at the college (SD�.26), female (77

percent), and drove cars on campus (81 percent).

Design

The experimental design is a single factor design (high ambiguity or low ambiguity)

with 20 participants randomly assigned to each condition. The experiment employed

the same procedure and instrumentation as Experiment 1.

Procedure

The procedure for this experiment mirrored the one used for Experiment 1. In order

to vary word ambiguity, the number of dictionary entries (Merriam-Webster’s

Collegiate Dictionary, 2003), or possible interpretations, for words within the text

of the article were counted (Rodd et al., 2000). Synonyms with more entries appeared

in the article with high ambiguity (from 7 to 11 entries, with an average 9 entries);

synonyms with fewer entries appeared in the article with low ambiguity (from 1 to 4

entries, with an average 2 entries). In both articles synonyms were provided for the

same words. Thirty-six words (approximately 10 percent of the total words in the

article) including nouns, verbs, and adjectives were varied.

All participants read and categorized the same interpretations from other students.

These interpretations came from the wide scope and negatively skewed distribution

induction in Experiment 1. We used a chi-square test to evaluate the measurement

model for this small sample, which it passed, x2 (df�116, N�40)�49.87, ns,

RMSEA�.07 [90 percent CI, .06�.08]. The measurement validity and reliability

showed no substantial changes from Experiment 1: article advocacy, Cronbach’s

a�.97, attitude toward topic, pretest Cronbach’s a�.98, posttest Cronbach’s a�.97,

change Cronbach’s a�.94, other’s credibility Cronbach’s a�.60.

Analysis

Correlations were used to test the two-step model. Z-scores were used to compare the

experimental conditions.


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Results

The social influence hypothesis coincided with these data. Participants’ predicted

social influence scores, their sum of frequency and range values, accounted for how

participants’ interpretations deviated from the control group’s interpretation as

expected. Participants reading the article with ambiguous synonyms evinced a strong

correlation between their social influence score and how their interpretations

deviated from the control group, r(18)�.64, pB.05. Those reading the article

with unambiguous synonyms showed a modest correlation, within sampling error of

zero, between their social influence score and their interpretation-deviations, r(18) ��.06, ns. As predicted, words with more ambiguity enhanced social influence,

z(38)�2.05, pB.05. Words with less ambiguity reduced this influence. Experimental

conditions and assessments of the others’ credibility had no substantial impact.

Participants’ deviations from the control group’s interpretation of the article

predicted how their attitudes toward new campus parking plan changed, r(37)�.41,

pB.05. The linear discrepancy model fit these data well. The correlation between

participants’ initial attitudes toward new campus parking plan and attitude change

was negative, r(37)��.32. Additionally, the autocorrelation between the initial and

final attitude reports was high (r�.80). Although not predicted, the relationship

between interpretation deviation and attitude change was stronger for those who read

the unambiguous article, r(18)�.56, pB.05, than for those who read the ambiguous

article, r(18)�.28, ns, although these differences were not statistically significant,

z (38)�1.01, p�.31. The correlations between the computed social influence scores

and attitude change was higher in the ambiguous condition, r(18)�.34, ns, than in

the direct condition, r(18)��.02, ns, but within sampling error, z(38)�1.09,

p�.28.

Discussion

As words present more ambiguity, the more people must use contextual information

to disambiguate them. Knowledge of how other people disambiguated these words

may be one such contextual feature. More than 60 years ago Asch wrote that social

influence may not just change how people evaluate objects, but influence what objects

people are evaluating. This study borrowed from a psychophysics theory to develop a

two-step model to predict how others might influence message perceptions. The

proposed two-step model coincided with how experimental participants interpreted

newspaper articles (differently from a control group) and subsequently changed their

attitudes. This model worked within a boundary condition: The words in the

newspaper article needed to possess some ambiguity. This boundary condition was

anticipated theoretically as an underlying assumption of this type of social influence.

Public Opinions

In a review of public opinion and communication research, Glynn, Ostman, &

McDonald (1995) noted that ‘‘the major implication is that individuals care what


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other think about public issues, form perceptions of what others think, and, to an

extent, modify their own opinions and/or behaviors on the basis of those

perceptions’’ (p. 254). Scholars dating back to Cooley (1902) have thought of such

influential others as ‘‘imaginary interlocutors.’’ Further, some applied circumstances

provide anonymous authors for interpretations, such as when those peer-reviewing a

medical malpractice suit are allowed to see how other doctors interpreted the

situation (as malpractice or not) before they read the case. Interestingly, participants

evaluated other (fictitious) students’ ratings as relatively credible. That said, the

interitem reliability was not strong, which may indicate that people do not blur

anonymous opinions into a cohesive sense of ‘‘others’’ or public opinion. Further

research into when and how learning of others’ opinions melds into a sense of public

opinion would be worthwhile.

Message ambiguity. In thinking about the boundaries of this type of influence

another issue arises. Increased message ambiguity may increase the cognitive load

people bear when reading messages. Indeed, people exhibit more frontal activity

when primed with more ambiguous words (Lee & Federmeier, 2006). Persuasion

theories that focus on how different amounts of cognition affect persuasive outcomes

may be bounded by the amount of ambiguity within the message. The amount of

cognitive work implied in disambiguating words in a message may impact dual-

processing theories of persuasion (e.g., elaboration likelihood model or heuristic

systematic model, see Eagly & Chaiken, 1993 for a review). When people need to look

to contextual cues to disambiguate words in a message, they may attend to these

peripheral cues more than if they do not need to disambiguate the message. The need

to disambiguate a message may also make processing the message feel more difficult,

thereby qualifying the potential utility, credibility, and involvement with the

message’s content. On the other hand, people may elaborate more on the words

and content of the message, because they need to disambiguate the message,

potentially encouraging more central processing. Future research may be able to

clarify when and how message ambiguity may interact with cognitions related to

persuasion.

Strategic ambiguity. Additionally, an important construct in organizational

communication, strategic ambiguity (Eisenberg, 1984), may be impacted. Strategic

ambiguity suggests the use of symbols for organizational values that possess some

ambiguity so that employees may make individual interpretations of these values and

think that other employees share these values. This suggestion attempts to balance

maximum individuality and organizational cohesion. Others suggest that to be

effective messages like public service announcements must be designed with strategic

ambiguity (DeJong, Wolf, & Austin, 2001). These studies and future work could

provide explanatory and pragmatic guidance for how messages may be designed with

strategic ambiguity and the consequences of this strategy for message effects. This

study’s second experiment provides insight into an interesting decision for message

designers: unambiguous messages may influence attitude change more noticeably

than ambiguous messages. Participants’ attitude change after reading the unambig-

uous message were considerably higher than the changes evidenced in ambiguous


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experimental conditions. Although ambiguous messages might seem like a reasonable

alternative to message designers who do not want to appear didactic, they might be

counterproductive.

These considerations depend on better understanding of what characteristics of the

audience may also inhibit or exacerbate this process. For example, the function served

in forming an attitude (e.g., Katz, 1960) may impact this process. In addition, if the

attitude serves a value-expressive function, then people may weight public opinions

with value-laden content more heavily than those without it, thereby influencing

both range and frequency values. In addition, social regulating factors, such as fear of

embarrassment, self-esteem, and social desirability, which impact inaccuracies in

perceiving public opinion (e.g., pluralistic ignorance, see Glynn et al., 1995 for a

review), may encourage people to seek more opinions before reading the message

themselves: more opinions, especially self-selected opinions, could impact range and

frequency values. Future research would benefit from the addition of such audience

variables.

Limitations

Three issues limit these findings: topic biases, time delay, and the ambiguity measure.

These article topics (course requirements, parking plans, and teaching assistants) all

pertain to university administrative decisions. All articles presented a negative bias

toward these topics. Most participants thought that a peer authored the articles.

These choices may influence what other contextual factors may be used for

disambiguation. For example, if participants read articles supporting these topics,

then they might guess that an administrator wrote the article, instead of a student. It

is possible that perceived propaganda from university administration, versus appeals

from their fellow students, may activate different semantic representations, thereby

influencing how the messages could be interpreted. In future studies this theoretical

premise could be tested with messages that vary in support (pro and con) and

authorship (someone other than the reader’s peer group).

In addition, experiments with longer durations of time between observations may

provide insight into the duration of attitude change. Without lengthier longitudinal

studies the long-term impact of changes in attitudes toward these issues remains

hidden. A pretest�posttest design allows for the opportunity to assess changes in

participants’ attitudes. This design may sensitize participants to the issues, and future

research might profit by using different designs to investigate such effects.

Although using the number of entries for each word in the dictionary has been a

useful way to generate semantic ambiguity (Rodd et al., 2000), it does not

discriminate between types of semantic ambiguity. For example, the word ‘‘strong’’

has twenty-one entries, whereas ‘‘cleave’’ has two. The entries for ‘‘strong’’ are all

relatively similar, for example: physically powerful, force of character, or effective

exercise of authority, etc. The entries for ‘‘cleave’’ are direct opposites, that is, to

adhere together or to split apart. In this case, the need to disambiguate a word like

‘‘cleave’’ from two opposite meanings may be more critical than disambiguating the

slight nuance in ‘‘strong.’’ Indeed, previous studies show that words with multiple,


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distinct entries, such as chosen in this study, delay recognition, while words with

multiple senses of the same entry improve recognition (Rodd et al., 2000). In

addition, abstract works have been shown to activate less stable representations than

concrete words (Plaut & Shallice, 1993), which may explain why contextual influences

may produce stronger effects on message perception and attitude change as seen in

experiment 2.

Sources for Disambiguation

Although others’ perceived credibility showed little impact on the model’s variables,

it is too early to suggest that anyone might serve as a source to disambiguate

messages. As noted by an anonymous reviewer, the participants were told that ‘‘other

university students’’ provided the opinions, which could have provided enough detail

to make them feel similar to the anonymous sources. This similarity could have

impacted perceived credibility through in-group biases (Brewer, 1979). It is possible

that providing more information about the other people constituting the public

opinion would alter perceived credibility as well as the influence of perceived

credibility in the message interpretation and attitude change process. This research

theoretically ties to the most recent work in bounded normative influence (Kincaid,

2004), explaining how new social norms diffuse within a community. ‘‘Bounded

normative influence is the tendency of social norms to influence behavior within

relatively bounded, local subgroups of a social system rather than the system as a

whole’’ (Kincaid, 2004, p. 38). Understanding direct (e.g., bounded normative

influence) and indirect (an disambiguation model) forms of social influence, and

their relative importance and interplay, remains an important topic for contemporary

scholarship to address.

In summary, the two-step model articulated in this paper shows promise for

explaining a subtle form of social influence. Sometimes, other people’s responses may

serve to disambiguate the meaning of words in a message, thereby influencing what

message people process. Glynn and colleagues (1995) argued that public opinion

research typically focuses on understanding the mechanisms underlying how

accuracy people perceive others opinions (e.g., pluralistic ignorance, third-person

effects, or false consensus, see Glynn et al., 1995 for a review) accuracy, and neglect to

consider how public opinion may serve as a contextual influence on people’s

perceptions of the issues at hand and their responses to them. This study provides an

initial framework by which to explain such processes.

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understanding the influence of others on perceptions of a message's advocacy: testing a...

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