Download The Role of Comparison Group Size in the Third

International Journal of Public Opinion Research Vol.  No. 
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THE ROLE OF COMPARISON GROUP
SIZE IN THE THIRD-PERSON EFFECT
David Tewksbury
ABSTRACT
Prior third-person effect research has demonstrated that the perceived discrepancy
between the impact of media messages on one’s self and others is driven by a number
of factors. For example, several studies have found that the size of the gap increases
as the ‘others’ become more socially remote from the perceiver. Unexplored until now
has been the independent influence of the number of others that people consider. It
may be that remote others are perceived to be more vulnerable to messages in part
because they are often a larger group of people. The results of two experiments support
this suggestion. Estimates of media influence on various others increased with group
size, the manipulated variable, in both between-subjects and repeated-measures tests.
With size held constant, estimates of effects also increased as the comparison group
became more socially and geographically distant.
Questions about the impact of messages in the mass media circulated for most
of the twentieth century. Early theorizing on the social effects of the media
predicted—or often assumed—that people were widely vulnerable to influence
by exposure to the media (see Delia  for a review of this literature). Toward
the middle of the century, early social scientific research on political persuasion
(e.g., Lazarsfeld et al. , Klapper ) revealed that the process of media
influence was far more subtle than people had thought. Rather than having a
major, direct impact on opinion, exposure to messages in the media tended to
merely activate and reinforce pre-existing dispositions. Research and theorizing
since then has been aimed at identifying the specific, focused sorts of social
effects the media may, indeed, have.
Communication researchers have noted that most people hold firm views
about the strength of the impact of the mass media. Third-person effect research
is one body of literature focused on what seem to be misperceptions about the
impact of exposure to the media. While most people see themselves as relatively
impervious to obvious manipulation by the media, they can easily imagine other
people being quite vulnerable (Davison ). This phenomenon has generated
This article was first submitted to IJPOR November , . The final version was received September
, . The author wishes to thank Deborah Weis and Amber Scott for their assistance in collecting the
data used in this project and the anonymous reviewers for their insightful comments.
 World Association for Public Opinion Research 

     
a significant amount of attention in the field. Research on the third-person
effect has demonstrated that people often report that others are more likely to
be influenced by exposure to the media than they are themselves (for a review,
see Perloff ).
A common finding in research on the third-person effect is that the width
of the gap between the perceived impact of media messages on oneself and
others increases as the ‘others’ become more geographically or socially remote
(e.g., Brosius and Engel , Cohen et al. , Gunther ). Cohen et al.
(), for example, reported a linear increase in effect estimates as the target
moved from other people at the respondents’ university to other residents of
their state and then to general public opinion. The phenomenon has come to
be called the social distance corollary of the third-person effect (McLeod et al.
).
What has thus far been missing from research in this area is a consideration
of the independent contribution of variations in the size of the comparison
group. While prior research has demonstrated that the social categories people
think about can affect their estimates of the effects of media messages, there
has been no systematic attempt to explore how the number of people they
consider can influence the judgment. There are many reasons to expect that
comparison group size should affect media impact estimates. Perhaps chief
among them is a deep Western cultural suspicion about crowds and other large
collections of people. To refer to a large number of people as a ‘mass’ has never
been a compliment (Price ). People often talk of the large group as one
step removed from a mob, prone to senseless, even violent action. Thus, the
twentieth-century equation of media audiences with mass audiences (see Webster
and Phalen  for a review of this process) was, in part, an implicit recognition
that media audiences are relatively senseless and vulnerable to persuasion.
Setting aside scholarly debates over the theoretical and empirical worth of mass
society models, it is important to note that the conceptual cousin of vulnerable
audiences is the faceless mass. It seems likely that, in popular thinking, the
larger the mass, the more vulnerable it appears.
Within the context of the third-person effect and public opinion research,
the key question is whether the number of message recipients that people
consider can influence how they think about the potential effects of the media.
The third-person effect hypothesis suggests that perceptions of the effects of
media messages will influence perceivers’ support for censorship and other
measures to limit dissemination of those messages (Davison ). Thus, any
factor that leads perceivers to exaggerated perceptions of media impact can
potentially increase popular support for media regulation (see Perloff , for
a review of studies linking effect perceptions with policy beliefs). Perceptions
of audience size seem relevant here in as much as they are variable and malleable.
That is, if people believe groups of varying size are differentially affected by
  

media messages, then popular support for restrictions of those messages may
be affected in turn.
This is certainly relevant for understanding public opinion on censorship
issues, and policy actors with an interest in these restrictions may even be able
to use perceptions of audience size in efforts to manipulate opinion. For example,
it may very well be that interest group efforts (such as those undertaken by
certain groups in the United States) to bring popular pressure on television
networks to reduce the amount of violence in their programming would benefit
from noting the large size of audiences. As part of demonstrating that many
people receive violent messages, these groups could influence popular perceptions
of the amount of influence audiences are experiencing. Naturally, these comments
are mere speculations. The starting point in exploring them is an examination
of the role of perceptions of audience size on media effect estimates.
SOCIAL DISTANCE AND THE THIRD-PERSON EFFECT
Because of a potentially close conceptual and empirical relationship between a
comparison group’s number and its social distance, previous research on the
effect of the latter should be relevant.1 One explanation of the social distance
effect suggests that its roots lie in basic social comparison and group differentiation processes (e.g., Duck and Mullin ). Social comparison theory
suggests that people experience a basic need to compare themselves to others
(Festinger , Tajfel and Turner ). As part of that comparison process,
they presumably evaluate the similarity between themselves and others on some
set of dimensions (Festinger ). Available evidence supports the idea that
perceptions of the similarity between oneself and others play a role in estimates
of message impact (e.g., Brosius and Engel , Duck et al. , , Duck
and Mullin ).
Recently, however, Eveland et al. () found that measures of perceived
similarity of others to respondents were unrelated to the social distance phenomenon. In fact, Eveland et al. () reported that the likelihood of others
being exposed to particular messages was a much more substantial predictor of
the social distance effect than was similarity. This finding underscores an
important point: what has been called social distance is likely not a single
dimension but a combination of several factors. In a  review of the
third-person effect, Perloff noted that social distance ‘. . . is a complex variable
that includes various components, such as perceived similarity, familiarity, and
1
Not all of the published research that has measured a social distance continuum has found a statistically
significant linear trend, of course (Cohen and Davis , McLeod et al. ). Cohen and Davis observed
a general increase in effect perceptions as the comparison group moved from fellow state residents to others
in the same region of the country and then to others in the United States. However, the pattern was not
statistically significant. McLeod et al. () concluded that a confound between social distance and perceptions
of groups’ likelihood of exposure to a message may account for their null findings.

     
identification’ (Perloff , p. ). But even that description may be understating the number of factors involved. Clearly, future work on this concept
needs to be explicit about the dimension of social distance being measured in
each case and how that factor fits within the overall distance phenomenon.
Perloff () suggests that the Cohen et al. () sort of operationalization of
social distance is assessing the impact of comparison group size and heterogeneity.
That is, by measuring students’ estimates of the effect of a defamatory news
article on other students at the university, other state residents, and public
opinion at large, their measure uniquely taps increases in group size. This may
not be the case, however. It seems more likely that this operationalization and
others like it (e.g., Brosius and Engel , Gibbon and Durkin ) are
confounding group size with some set of social similarity dimensions. As the
target group moves on a continuum away from the self, the group often becomes
both larger and more socially distant.
Most references to the target other in this area of research mention people
without specifying their number (e.g., Cohen et al. , Duck et al. ).
Third persons have been measured as individuals in several studies, however
(e.g., Gunther and Hwa , Hoorens and Ruiter ). Duck and Mullin
() demonstrated that with comparison group size held constant at one,
social distance exerted an independent effect on message impact estimates.
However, no prior study has varied the size of the target other. Consequently,
it is not clear whether third-person biases would have been more pronounced
had subjects considered more than one person in the target group. What is
more, no prior study has simultaneously manipulated group size and social
distance.
HYPOTHESES
The following hypotheses were formulated for examination.2 The results reported by Duck and Mullin () suggest that comparison group distance
(with its many dimensions) will have an effect when the comparison group size
is one. The present study extends that finding to a different setting and to
situations in which group size is manipulated. Thus, the first hypothesis states:
Holding group size constant, the gap between the impact of messages on target
groups and the self will increase as the social distance of the group increases.
The second hypothesis suggests that comparison group size will have an
2
Most studies of the third-person effect include an explicit hypothesis regarding the presence of a gap
between subjects’ estimates of media effects on themselves and their estimates regarding others. Because
such a test is relatively uninteresting in the present study, and because the basic phenomenon is so well
documented (Paul et al. , Perloff ), that hypothesis was omitted from the present research. It should
be sufficient to note here that biased third-person perceptions were found for each of the message scenarios
tested in the experiments reported here.
  

independent effect on message impact estimates: Holding social distance constant, the gap between the impact of messages on target groups and the self
will increase as the size of the group increases.
Most measurements of third-person perceptions ask respondents to consider
the effects of messages on some group of ‘others’ or ‘people’ (e.g., Cohen et al.
, Gibbon and Durkin ). What is unclear from these operationalizations
is the number of people respondents tend to consider when they make their
estimates. Thus, a general research question is this: What comparison group
size most closely approximates the group size assessed by the common unspecified
‘others’ measurement?
EXPERIMENT 
An initial mixed model experiment was used to test the hypotheses. All
subjects completed self-administered questionnaires during normal class periods.
Subjects were randomly assigned to one of four conditions. In the control
condition, subjects were asked to estimate the effect of exposure to Internet
pornography on themselves, a typical group of university students, a typical
group of state residents, and a typical group of Americans. Subjects in the
remaining three conditions estimated the effects of exposure on , , or 
person in each category. Thus, the resulting data can be analyzed on a
between-subjects basis in terms of the effect of group size. They can also be
examined on a within-subjects basis to determine whether the size of the
perceptual differential is affected by holding the comparison group size constant,
as is the case within each of the conditions.
S  M
A convenience sample of  students was recruited from undergraduate
communication courses at the University of Illinois at Urbana-Champaign.
These introductory courses tend to attract students from across the university
and primarily enroll first- and second-year students. The sample contained
more females than males ( percent female).
All subjects read a short description of the Internet pornography issue and
completed four effect estimates. The introductory description read as follows:
Many people are concerned about the amount of sexually explicit material available
on the Internet. The primary concern critics have is that users of the World Wide
Web may be accidentally exposed to sexually-oriented words and images. The fear
is that this inadvertent exposure may affect users’ moral values concerning sex.
The first effect estimate question for all subjects read, ‘Imagine you were

     
accidentally exposed to sexually explicit content on the Internet. How much
do you think you would be influenced by this sort of exposure?’3 Responses
were given on a -point scale with  (‘not influenced at all’) and  (‘influenced
a great deal’) as anchors. Subjects were then asked to estimate the amount of
influence that exposure may have on three groups of others. The questions in
the control condition read as follows:
Imagine a group of typical University of Illinois students (typical Illinois residents,
typical Americans) was accidentally exposed to sexually explicit content on the
Internet. How much do you think these people would be influenced by this sort of
exposure?
Responses were given on the -point scale used for self-estimates. Subjects in
the experimental conditions read questions slightly altered to manipulate group
size. In the  person condition, for example, inserted after ‘students’ in the
question above was the note, ‘(say, about  such students)’.4 The data used
for hypothesis testing were reduced through the calculation of differences
between respondents’ estimates of message effects on others and the effects of
messages on themselves.
R
Figure  plots the mean difference scores for all of the conditions. The data
were initially analyzed in a  (evaluation target) by  (target group size) mixed
model analysis of variance. This analysis omitted the control condition.5 The
ANOVA results failed to detect an interaction between experimental condition
and the repeated measures, F(, )=., p=.. Thus, it appears that
comparison group identity and size may be orthogonal factors. As predicted by
hypothesis , there was a main effect of the target group, F(, )=., p<
., 2=.. The polynomial linear and quadratic contrast tests were also
significant, Fs(, )=. and ., ps < ., 2s=. and ., respectively.
As the target of estimates moved from students to other Americans, effect
estimate differences increased in size, even with the size of the target group
held constant (as it is with this design). Repeated contrast tests indicated that
state resident-self differences were larger than students-self differences (F(,
3
Recent research has noted that traditional third-person effect research use of general influence measures
of this sort may be problematic (Salwen and Dupagne , Shah et al. ). Given the present study’s
emphasis on differences in the size of perceptual gaps, however, the present method of measuring effect
estimates should be adequate.
4
As two of the reviewers noted, this manipulation of group size is rather artificial. In future research, it
might be preferable to manipulate size through reference to naturally occurring social groups that are similar
to one another but differ in size.
5
The control group stimuli for target groups left the question of group size unspecified.
  

F  Internet pornography effect differences—reference target by group size (Experiment )
)=., p< ., 2=.), and American-self differences were larger than
those dealing with state residents (F(, )=., p< ., 2=.). In sum,
then, the data support the first hypothesis.
The second hypothesis predicted a main effect of comparison group condition.
As expected, comparison group size exerted a significant main effect, F(,
)=., p< ., 2=.. Polynomial contrast tests indicated the presence
of a linear relationship between target group size and effect estimates, F(,
)=., p< .. Contrast tests revealed that mean estimate differences
about  others were significantly larger than differences referencing  others
and  other, Fs(, )=. and ., p=., and p< ., respectively.
However, differences in subjects’ estimates about  persons were not significantly larger than those made about  person, F(, )=., p=.. In
summary, it appears hypothesis  was supported. A clear trend was observed,
but the distinctions between the two smallest comparison groups were not
statistically significant.
The research question in this study concerns the location of the control
group’s effect estimates relative to those given by the experimental groups. Post
hoc analyses using the perceptual difference scores are only somewhat helpful
in answering this question. The relatively conservative Scheffe tests failed to
detect any differences between the control group and the other conditions. The
less stringent Least Significant Difference tests indicated that the gap between
the control and the single-person group was significant for the student-self

     
differences (p=.) and marginally significant for the state resident-self differences (p=.). Obviously, these results are inconclusive. It appears from Figure
 that estimates in the control group are closest to those offered by the group
making judgments about  people, but this pattern cannot be confirmed
statistically.
D
The data presented here demonstrate rather clearly that the size of the
comparison group does make a difference in third-person perceptions. When
subjects made assessments about the impact of Internet pornography on others,
they were influenced by the size of the comparison group. The results supported
the hypotheses, but they raised two additional questions. The first is whether
the effect of comparison group number is somehow uniquely connected with
the Internet pornography scenario used here. Prior third-person effect research
has demonstrated that the tendency to overestimate the effects of messages on
others varies widely from message type to message type (e.g., Price et al. ,
Thorson and Coyle ). Thus, it was necessary to examine this process in a
different subject domain. Additionally, Experiment  looked at comparison
group size only in terms of a between-subjects test. It might be that people
exhibit a group size effect only when they are unaware of having made a
distinction between group numbers. Making the comparison explicit may expose
the logical problems inherent in their biased estimates. Observing the group
size phenomenon in a more overt setting will demonstrate its robustness. A
second experiment was conducted to examine these issues.
EXPERIMENT 
M
A mixed model experiment was used to replicate and extend the results of the
first study. The two hypotheses from the previous study were still relevant,
and a new research question was added: Will subjects make a distinction between
groups of different size when the comparison is explicit? Four media message
scenarios and accompanying effect estimates were placed in the main body of
a questionnaire. The first two scenario sets were employed in a between-subjects
replication of Experiment . Subjects were randomly assigned to one of the
four original conditions. The rest of the questionnaire contained the stimuli
and repeated measures items used to examine within-subjects effects.
A convenience sample of  students was recruited from undergraduate
communication courses at the University of Illinois at Urbana-Champaign. As
with the first experiment, the sample contained more females than males (
percent female).
  

The Internet pornography stimulus paragraph was retained from the first
experiment. A slight change in the wording of the effect estimate questions was
made in an effort to highlight the differences between this and the second part
of the study. After the paragraph describing the sexually explicit content issue
and the self-effect estimate question, the questionnaire included the following
statement (the particular wording is for subjects in the -person condition):
For each of the categories below, think about how much accidental exposure to
sexually explicit content on the Internet would affect a large group of people (about
 or so).6
The wording was slightly altered in the different conditions to communicate
group size. The three questions that followed asked subjects to estimate the
effect of exposure on typical students at their university, on typical residents
of their state, and on typical Americans. An identical procedure was used to
assess perceptions of the effects of exposure to violence in films. The experimental
condition for each subject was the same as that used in the Internet pornography
scenario. For each of the two scenarios, third-person perception scores were
calculated by subtracting estimates about the self from those about other people.
Two additional scenarios were added as part of a test of within-subjects
group size effects. The first described a hypothetical National Enquirer article
that accused actor/director Kevin Costner of skimming funds from a charity.7
The second described concerns that cigarette advertising may influence public
attitudes about smoking and its health risks. The effect estimates for these
scenarios followed a different measurement strategy than before. The subjects
in the three experimental conditions (i.e., those making estimates about , ,
or  people) made judgments about only fellow university students.8 After
reading each scenario, subjects estimated the effect of the media content on
themselves,  students,  students, and a single typical student.9 Perceptual
6
The wording of the section was changed in this way to distinguish between estimates about different
groups of people of the same number and, in the next section, estimates about different numbers of a common
group of people. Separating the numerical information from the group identity was intended to simplify this
transition from Part  to Part .
7
Gunther () has demonstrated that the credibility of a news source does not affect the operation of
the social distance phenomenon.
8
In the control condition, the message effect questions about the two additional scenarios followed the
same format as with the initial two. These responses served as a check on the size of standard third-person
perceptual differences for the latter two stimuli. For both scenarios, the control group’s mean differences
between estimates about the self and other university students approximated those observed in the other
conditions regarding larger groups of students (Ms=. and .; SDs=. and .; National Enquirer and
cigarette advertising scenarios, respectively).
9
The group size in the first of these questions for each subject mirrored the group size referenced in the
first two scenarios. The order of the other two questions was adjusted. For example, subjects in the
single-person group made estimates about , , and  fellow students, in that order. Interaction tests
within ANOVAs indicated no effect of estimate order.

     
F  Internet pornography effect differences—reference target by group size (Experiment )
difference scores were calculated for each subject by subtracting the self-estimates
from each of the three other estimates.
R: B-S E  G I  S
Figure  presents data for the group size and identity effects vis-à-vis sexually
explicit Internet content. As the plot of the perceptual difference scores suggests,
there is again substantial support for the social distance corollary, F(, )=
., p< ., 2=.. As before, polynomial contrast tests indicated the
presence of both linear and quadratic patterns in the data, Fs(, ) > , ps
< ., 2s > .. While the distance between the students-self and the state
residents-self differences was large (F(, )=., p< ., 2=.), there
was relatively little gap between the residents-self and Americans-self differences,
F(, )=, p=., 2=.. Nonetheless, there is ample support for hypothesis  here. As in Experiment , there was no interaction between this factor
and the group size manipulation, F(, )=., p=..
The data presented in Figure  show an unexpected twist in the effects of
the group size manipulation (relevant to hypothesis ). While the experimental
condition did have a marginally significant overall impact on subjects’ perceptual
differences, F(, )=., p=., 2=., the only significant gap detected
by the contrast analyses was between estimates about  people and about
, F(, )=., p=.. Thus, this is only a weak replication of the original
results.
  

F  Film violence effect differences—reference target by group size (Experiment
)
The data for the film violence scenario, shown in Figure , provide much
more substantial support for the hypotheses. There was an overall effect of
comparison group identity that followed the predicted pattern, F(, )=
., p< ., 2=.. Again, there were linear (F(, )=., p< .,
2=.) and quadratic trends in these data (F(, )=., p< ., 2=
.). The gap between the fellow students-self and state residents-self differences
was significant (F(, )=., p< ., 2=.), as was the one between
residents-self and the Americans-self differences (F(, )=., p< .,
2=.). In summary, hypothesis  is amply supported.
More importantly, the group size effect that was muted in the previous
scenario is much stronger here (overall F(, )=., p< ., 2=.). As
was the case in the first experiment, contrast analyses indicated a linear increase
in message effect difference scores as the comparison group grew (F(, )=
., p< .). The estimate differences regarding  people were significantly
larger than those about  and single others (Fs(, )=. and .,
respectively, ps < .), however there was no significant difference between the
latter two (F(, )=., p=.). Comparison group identity and size did
not interact (F(, )=., p=.). In summary, the data from the film
violence scenario replicated the results of Experiment  almost to the letter. As
the comparison group became more socially remote, the size of the perceptual
bias increased. More important for this study, as the comparison group size
increased so did the difference between effect estimates about the self and
others.

     
T  Effect estimates as a function of student comparison group size
Message type
Self

student

students

students
Costner accusations
.
(.)
.
(.)
.
(.)
.
(.)
.
(.)
.
(.)
.
(.)
.
(.)
Cigarette advertising
F
p
.
.
.
.
Note: Cell entries are means of differences between self effect estimates and estimates about other university
students. Entries in parentheses are standard deviations.
R: W-S E  G S
Subjects’ mean estimates of the effects of the Costner article and cigarette
advertising are presented in Table . The question for these data is whether
subjects’ estimates of message effects varied as a partial function of comparison
group size when the size comparisons were explicit. The estimates of message
effects on others were examined in parallel within-subjects analyses of variance.
Polynomial contrast tests of estimates of the effects of the Costner article found
a linear increase in estimates as group size increased, F(, )=., p< .,
2=.. While there were only weak differences between estimates about  and
 students (F(,)=., p=., 2=.) and between  and  students
(F(, )=., p=.), subjects believed  students were more likely to
be influenced than was a single student, F(, )=., p< ., 2=..
This pattern was found also in the data from the cigarette advertising scenario.
In that case, polynomial contrast analyses revealed a significant linear trend,
F(, )=., p< ., 2=.. Subjects’ tendency to report that  students
were more vulnerable than a single student was only marginally significant (F(,
)=., p=., 2=.). However, subjects reliably reported that 
students were more vulnerable than  students (F(, )=., p< .,
2=.).
D
In general, the results of Experiment  replicate and extend those obtained in
the first study. Both hypotheses received support. Subjects who made estimates
about the effect of media messages reported larger differences between themselves
and others as the size of the comparison group increased and, independently,
as the group became more remote. The research question was answered in the
affirmative. The group size effect was seen even when the size comparisons
were made explicit to subjects. Relevant to hypothesis , it should be noted
that the results of the sexually explicit Internet content scenario were somewhat
  

different than those obtained in Experiment . However, the estimate gap
regarding  others was still marginally larger than that about  others, a
conceptual replication of the first study. Still, it is important to note that the initial
group size pattern and strength of association were not exactly reconstructed for
that scenario. This suggests the need for more research to map the conditions
and parameters of group size effects in third-person perception.
GENERAL DISCUSSION
Overall, these experiments find that comparison group size exerts a significant,
and often substantial, impact on subjects’ perceptual biases. It is important to
remember that this effect of comparison group size does not account for the
social distance phenomenon, however. With group size held constant within
conditions in both experiments, subjects demonstrated a strong tendency to
estimate larger effects as social distance increased. In addition, the results held
no sign of an interaction between the size and distance manipulations used in
these experiments. Thus, the results of this study suggest that it may be useful
to think of comparison group size as a separate, independent contributor to
how people estimate the effects of media messages, one that occurs in addition
to the effect of social distance.
Naturally, there are some limitations to the present study, and these concerns
should be kept in mind. It is often a good idea to include a check on the success
of manipulations used in experiments. Unfortunately, no such checks were
available here. In addition, the subjects used in this research were undergraduate
students, and it is possible that students differ from other people in ways that
are consequential for the phenomena studied here. It is important to note,
however, that the third-person effect has repeatedly been observed among
non-student samples (e.g., Brosius and Engel , Davison , Gunther
, Shah et al. , Salwen ), and there is no obvious reason to believe
that the group size effect would be a feature that is unique to student perceivers.
While the presence of an effect of comparison group size is relatively well
demonstrated here, more research is needed to identify the psychological forces
at work. Henriksen and Flora () have suggested a similarity between the
social distance phenomenon and a ‘person-positivity’ bias (Sears ). This
phenomenon may offer some insight into the role of group size. Sears suggested
that people evaluate others in terms of their perceived ‘personhood’ (, p.
), the degree to which they are more like distinct individuals than like
impersonal aggregates or groups. He reported that subjects in an experiment
rendered more favorable judgments of individuals than of aggregates of the
same individuals. It may be that a similar process is at work in the social
distance corollary. As the size of the group increases, people may judge the
members of the group to be farther away on a personhood dimension and so

     
be less similar to them. From this perspective, the group size effect observed
in the present study is a unique element of a larger social comparison process.
Empirically, the person-positivity effect has only been observed with respect to
comparisons between one person and a group of people (Miller and Felicio
). Miller and Felicio reported that subjects’ reports of liking for groups of
others did not vary as a function of the target group size (). Thus,
person-positivity may offer some insights into the group size effect, suggesting
that it is part of a process of interpersonal similarity perception. However, there
is also some evidence that it may not provide a complete explanation.
A second phenomenon that may shed light on the process is known as the
set-size effect (Anderson , Kaplan , Sloan and Ostrom ). Research
in interpersonal evaluation has found that as the number of attributes describing
other people grows, perceivers’ evaluations of those people become more
polarized. For example, Anderson () reported that when target others were
described with a set of adjectives, subjects rendered more extreme evaluations
(e.g., both positive and negative) as the adjective set size grew larger. Researchers
have suggested that subjects’ confidence in their opinions grows with the amount
of information they have about others and so they tend to render stronger
judgments (Kaplan ). Similarly, Willis () reported greater polarization
in judgments of groups of people when the size of the group was increased.
The fundamentals of this process may apply to the group size effect observed
in the present research. It may be that subjects’ ego-enhancing tendency to
denigrate the target group grows more extreme (i.e., estimates of effects grow
larger) as the size of the comparison group increases. From this perspective,
the effect of comparison group size reflects a perceptual phenomenon set within
a larger group-identity process. That is a somewhat different account of the
third-person effect than is usually told. Most explanations of third-person
perceptions focus largely on ego-enhancement motivations. A story that integrates the set-size phenomenon would need to increase the emphasis placed
on elements of perceptual accuracy and other cognitively ‘cold’ processes. To
be sure, some researchers have examined the role of personality and media
orientations in the third-person effect (e.g., Price et al. ), but these efforts
have not been entirely fruitful. Unfortunately, there is too little data available
here to decide how much weight to give to this newer explanation.
It also might be that the comparison group size dimension of social distance
is evidence of an as-yet unexplored process in third-person perception and
measurement. It may be that as people consider the effect of messages on others,
they equate magnitude of influence with the number of people influenced. That
is, respondents in third-person effect studies may be thinking of many people
being influenced as an indication that a large amount of influence has occurred.
Thus, it may be that third-person effect research has been tapping, in part, a
perception that part of a message’s ultimate impact lies with the number of
  

people affected. This reasoning is certainly plausible within the confines of
methods often used to measure third-person perception and social distance.
For example, Cohen et al. () asked subjects to estimate how much a
newspaper article ‘would affect the opinions of’ other students and so on (Cohen
et al. , p. ). Within the concept of affecting opinions lies room for the
equation of magnitude with number. Other studies looking at social distance
have featured similar measures of perceived message impact (e.g., Eveland et
al. , Gunther ). Certainly, this explanation does not explain why, in
the present case and as reported by Duck and Mullin (), people perceived
greater effects along a social distance scale even when group size was held
constant. However, it may provide some insight into how people think about
message effects. At the very least, it might be useful to look at this possibility
in future research on the third-person effect.
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BIOGRAPHICAL NOTE
David Tewksbury is an assistant professor in the department of Speech Communication
and the department of Political Science at the University of Illinois at UrbanaChampaign. His research interests include the third-person effect, the reception and
effects of news delivered via the Internet, and the cognitive processing of news messages.
Address correspondence to David Tewksbury, Department of Speech Communication,
University of Illinois at Urbana-Champaign,  S. Wright St., Urbana, Illinois ,
USA, Email: [email protected]