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Third-Person Effect and Censorship
of Web Pornography
By Li-jing Arthur Chang
Li-jing Arthur Chang
Assistant Professor
Department of Mass Communications
Jackson State University
P.O. Box 18590
Jackson, MS 39217-0990
Tel: (601)979-1351
Email: [log in to unmask]
Submitted to:
Mass Communication and Society Division
Association for Education in Journalism and Mass Communication
Dr. Renita Coleman
MC&S Division Research Chair
Manship School of Mass Communication
Louisiana State University
Baton Rouge, LA 70803-7202
April 1, 2005
Abstract
The study, which surveyed 710 respondents in Singapore, found that
third-person effect played a role in the support for the censorship
of Web pornography. Other factors found to predict the support for
the censorship measure include gender, age and Internet use. In
addition, the study also confirmed past empirical evidence about the
link between third-person effect and undesirable media content, and
the association between third-person effect and the social distance
between self and others.
Introduction
Censorship of Internet pornography has been an issue receiving high
attention in many parts of the world, as research has indicated
sexually explicit media content may affect the behaviors of teenagers
(Collins, Elliot, Berry, Kanouse, Kunkel, Hunter & Miu, 2004). In
Asia, which has the highest number of Internet users among the major
regions in the world (Internet World Stats, 2004a),[1] many countries
have scrambled to limit public access to Web pornographic materials
(Fluendy, 1996). Inside Asia, Singapore is an interesting case
because it has one of the highest Internet penetration rates in the
continent (Internet World Stats, 2004b). Despite its effort to
promote Internet usage, the Singapore government is concerned about
the negative impact from the online media on the public and has tried
hard to block public access to pornographic Web content (Ang &
Nadarajan, 1996).
As research showed that censorship of pornography has received
widespread support in Singapore (Ang et al., 1996; Gunther & Ang,
1996), it would be interesting to study the reasons behind the
general public's support for the censorship, especially in the case
of censorship for Web pornography – an issue of great public concern.
As no prior study seems to have explored the general public's
opinions about their reasons behind supporting the censorship of Web
pornography, findings from the study will be useful for policy makers
coping with the censorship issue.[2]
Research has shown many in the public favor censorship for
potentially harmful media content because they believe others may be
more susceptible to the negative impact of such content than they are
(Gunther, 1995; Gunther et al., 1996; Hoffner & Buchanan, 2002;
Hoffner, Buchanan, Anderson, Hubbs, Kamigaki, Kowalczyk, Pastorek,
Plotkin & Silberg, 1999; McLeod, Eveland & Nathanson, 1997; Rojas,
Shah & Faber, 1996; Salwen, 1998; Salwen & Dupagne, 1999; Wu & Koo,
2001). The concern that others, rather than oneself, may be more
vulnerable to harmful media effects was first coined by Davison
(1983) as the third-person effect, also known as the perceptual bias
between self and others regarding the vulnerability to undesirable
media content.
As third-person effect has been found in the past to predict support
for censorship of undesirable media messages (Gunther, 1995; Gunther
et al., 1996; Hoffner et al., 2002; Hoffner et al., 1999; Lo & Wei,
2002; McLeod et al., 1997; Rojas et al., 1996; Salwen, 1998; Salwen
et al., 1999; Wu et al., 2001), the present study intends to explore
how the intriguing concept of third-person effect affects the levels
of public support for censoring Web pornography in Singapore. In
addition, the study attempts to probe the influence of other factors
found in the past to predict censorship of undesirable media content,
such as gender (Chia, Lu & McLeod, 2004; Gunther, 1995; Gunther et
al., 1996; Hoffner et al., 1999; Rojas et al., 1996), age (Gunther et
al, 1996; Hoffner et al., 1999; Rojas et al., 1996; Wu et al., 2001),
education (Hoffner et al., 1999; Lo et al., 2002; Salwen, 1998;
Salwen & Driscoll, 1997; Salwen et al., 1999), and media use (Chia et
al., 2004; Gunther, 1995; Hoffner et al., 1999; Lo et al., 2002;
Salwen et al., 1997; Wu et al., 2001).
Literature Review
According to a synthesis of past research, factors predicting public
support of censorship against undesirable media messages (e.g., media
violence, pornography, etc.) include third-person effect (Gunther,
1995; Gunther et al., 1996; Hoffner et al., 2002; Hoffner et al.,
1999; McLeod et al., 1997; Rojas et al., 1996; Salwen, 1998; Salwen
et al., 1999; Wu et al., 2001), gender (Chia et al., 2004; Gunther,
1995; Gunther et al., 1996; Hoffner et al., 1999; Rojas et al.,
1996), age (Gunther et al, 1996; Hoffner et al., 1999; Rojas et al.,
1996; Wu et al., 2001), education (Hoffner et al., 1999; Lo et al.,
2002; Salwen, 1998; Salwen et al., 1997; Salwen et al., 1999), and
media use (Chia et al., 2004; Gunther, 1995; Hoffner et al., 1999; Lo
et al., 2002; Salwen et al., 1997; Wu et al., 2001).
Third-Person Effect
Third-person effect was first coined by Davidson (1983) as the
perceptual bias about the impact of undesirable media messages on
others vs. on oneself. Specifically, the third-person effect
hypothesis postulates that people in general perceived undesirable
media messages (e.g., propaganda) will have greater effects on other
people than on themselves (Davidson, 1983; Gunther & Mundy, 1993;
Mason, 1995; Price, Huang & Tewksbury, 1997; Salwen & Dupagne, 2001).
Since Davison first proposed the third-person effect, at least 45
published studies have tested the concept and found support for its
existence (Perloff, 1999). According to the research, whether the
undesirable messages is media violence (Duck & Mullin, 1995; Innes &
Zeitz, 1988), negative political advertising (Cohen & Davis, 1991),
or pornography (Gunther, 1995), people tend to believe others will be
more susceptible to the impact of such messages (Perloff, 1999).
Applying the above empirical evidence in the present research, it is
possible that the perceived effect of Web pornography on self (i.e.,
an adult in Singapore) is going to be less than the perceived effect
of Web pornography on other adults in Singapore. Or, put another way,
the perceived effect of Web pornography on other adults is likely to
be greater than the perceived effect of Web pornography on self.
Based on this rationale, the first hypothesis for the present study
is generated:
H1: The perceived effect of the Web pornography on other adults will
be greater than the perceived effect on self.
Research has also shown that the greater the social distance between
oneself and others, the greater the third-person effect (Chia et al.,
2004; Cohen, Mutz, Price & Gunther, 1988; Duck, Hogg & Terry, 1995;
Gibbon & Durkin, 1995; Gunther, 1991; McLeod et al., 1997; Lo et al.,
2002; White, 1997). For example, Cohen et al. (1988) found the size
of third-percent perception increased as the social distance between
self and others became wider. Subjects believed the impact on
"others" will grow bigger when "others" changed from "other Stanford
students" to "other Californians" to the public at large (Cohen et
al, 1988). Similarly, McLeod et al. (1997) discovered from a research
on a group of mass communication majors in a Delaware university that
the third-person effect turned larger when the definitions of
"others" changed from "Delaware students" to "New York/Los Angeles
youth" to "average person."
Applying the social distance hypothesis in the current study, it is
possible that the third-person effect will be greater when the social
distance becomes wider. For example, according to the social distance
hypothesis, when the "others" in the current study changed from
"other adults" to "young people" in Singapore, the third-effect will
become larger. Following this rationale, the second hypothesis is generated:
H2: The size of third-person effect will increase as the social
distance of the comparison group increases (i.e., when "others"
change from "other adults" to "young people").
Past research on the impact of undesirable media content also showed
that third-person effect is closely related to public support for
censorship of such content (Gunther, 1995; Gunther et al., 1996;
Hoffner et al., 2002; Hoffner et al., 1999; Lo et al., 2002; McLeod
et al., 1997; Rojas et al., 1996; Salwen, 1998; Salwen et al., 1999;
Wu et al., 2001). As the third-person effect is really reflecting the
phenomenon that the perceived negative media effect on others are
greater than the perceived negative effect on oneself, it would be
interesting to see if perceived negative media effect on others would
be a stronger predictor behind the support for censoring Web
pornography, compared to the perceived media effect on self. As the
potentially harmful media content tested in the current study is Web
pornography, perceived effect of Web pornography on self and
perceived effect of Web pornography on two groups of others (i.e.,
other adults in Singapore and young people in Singapore) can be
tested as predictors for public support to censor Web pornographic
content. Based on the above rationale, the following research
question is generated:
RQ1: How do the levels of public support for censoring Web
pornography affected by perceived negative effects of the Web
pornography on oneself, other adults and young people?
Research testing the influence of third-person effect on public
approval for censorship also found other factors, along with
third-percent perception, are behind the support for censorship of
undesirable media massages. These factors include gender (Chia et
al., 2004; Gunther, 1995; Gunther et al., 1996; Hoffner et al., 1999;
Rojas et al., 1996), age (Gunther et al, 1996; Hoffner et al., 1999;
Rojas et al., 1996; Wu et al., 2001), education (Hoffner et al.,
1999; Lo et al., 2002; Salwen, 1998; Salwen et al., 1997; Salwen et
al., 1999), and media use (Chia et al., 2004; Gunther, 1995; Hoffner
et al., 1999; Lo et al., 2002; Salwen et al., 1997; Wu et al., 2001).
Gender
Compared with men, women are more likely to support restrictions on
pornography (Herman & Bordner, 1983; U.S. Commission on Obscenity and
Pornography, 1970). Several researches testing the influence of
third-person effect on censorship support also found gender as a
significant predictor behind public approval for the censorship of
undesirable media content (Gunther, 1995; Gunther et al., 1996;
Hoffner et al., 1999; Lo & Wei, 2002; Rojas et al., 1996).
Specifically, the studies showed women are more likely than men to
support the censorship of undesirable media content, such as TV
violence (Gunther et al., 1996; Hoffner et al., 1999) and pornography
(Gunther, 1995; Lo et al., 2002; Rojas et al., 1996).
Age
Some past researches testing the impact of third-person effect in
censorship support also found that age can be another predictor of
public approval for censorship (Gunther et al., 1996; Hoffner et al.,
1999; Rojas et al., 1996; Wu et al., 2001). For example, Gunther et
al. (1996) and Hoffner et al. (1999) found out that age is a
predictor behind the levels of public support for censoring TV
violence. In addition, two studies conducted based on samples from
universities students (Rojas et al., 1996; Wu et al., 2001) also
discovered older students, compared with their younger counterparts,
are more in favor of censorship measure of undesirable media content.
Education
There is also evidence showing education could be a good predictor
behind public support for censoring undesirable media content (Lo et
al., 2002; Salwen et al., 1997; Salwen, 1998; Salwen et al., 1999).
Surveys on adults in the United States (Salwen et al., 1997; Salwen,
1998; Salwen et al., 1999) showed education has a negative
relationship with support for censorship of media content. However, a
survey on high school and university students (Lo et al., 2002) found
out that older students tend to support censorship of Web pornography.
Media Use
Past research has shown that media use as a predictor affecting the
levels of public support for censorship measures against undesirable
media messages (Chia et al., 2004; Gunther, 1995; Hoffner et al.,
1999; Lo et al., 2002; Salwen et al., 1997; Wu et al., 2001).
The term media in the case of the present study means the Internet.
Presumably, people who use more Internet content will be less likely
to support censorship of Web content. This assumption coincides with
evidence from studies by Lo et al. (2002) and Wu et al. (2001), who
found that exposure to Internet pornography tends to reduce support
for restrictions on such Web content. The above assumption and
empirical evidence suggest that it is possible the Internet usage may
reduce support for censoring Web pornography.
According to the above review, besides the third-person effect,
gender, age, education and Internet usage may be other factors
predicting the levels of public support for restricting Web
pornographic content. Therefore, a second research question is generated:
RQ2: How do the levels of public support for censoring Web
pornography affected by factors such as gender, age, education and
Internet usage?
Method
Sampling
Data for this study was collected in face-to-face interviews with 710
adults (aged 18 or older) in Singapore from April to May, 2001.[3]
The 710 subjects with complete responses to the survey questionnaire
are from the original sample pool of 1447 households. Given the
procedure to randomly select one adult per household for interview,
the completed 710 questionnaires represent a response rate of 49.1%.
The original sample pool of 1447 households was randomly selected
through stratified sampling, a probability sampling procedure to
ensure the subjects are randomly selected in Singapore. Specifically,
the area in the country is divided into clusters, stratified for
geographical locations, housing types and socio-economic classes. A
number of clusters were randomly selected and a number of households
inside the selected clusters are also randomly chosen. Finally,
inside each chosen household, an interviewee was randomly selected.
The whole procedure was designed to ensure all the interviewees were
randomly selected.
Operational Definitions
The interviews went on for about half an hour for each subject
completing a questionnaire. The questionnaire items covers all
concepts tested for this research: (1) negative effect of Web
pornography on self, (2) negative effect of Web pornography on other
adults, (3) negative effect of Web pornography on young people, (4)
third-person effect, (5) support for censorship of Web pornography;
(5) demographics (gender, age and education), and (6) time spent
weekly on the Web.
Negative effects of Web pornography on self, other adults and young
people. For the measurements of the three variables (i.e., negative
effect of Web pornography on self, negative effect of Web pornography
on other adults, and negative effect of Web pornography on young
people), the respondents were asked to indicate on a 4-point Likert
scale (with "not at all" at one end of scale and "a great deal" at
other end) the amount of influence Internet pornography on self,
other adults and young people. The responses to the Likert scale was
coded as follows: "not at all" was coded "1," "a great deal" was
coded as "4," and the answers in between two polarized responses were
coded as "2" and "3" accordingly.
Third-person effect. The measurement of the third-person effect is
derived by comparing the difference between the negative effect of
Web pornography on self and the negative effect of Web pornography on
others. As the second hypothesis of the present study is aimed to see
how third-person effect may change when the social distance between
self and others widens, there are two types of "others" in this case:
the first others is "other adults," and the second others is "young
people," with the latter having wider social distance with "self."
Therefore, third-person effect between self and others as other
adults was derived by subtracting negative effect of Web pornography
on self from negative effect of Web pornography on other adults.
Similarly, third-person effect between self and others as young
people was derived by subtracting negative effect of Web pornography
on self from negative effect of Web pornography on young people.
Demographics (gender, age and education). During the face-to-face
interviews for the present study, interviewees' genders, age
categories[4] and education levels were also recorded. The responses
to the gender question were coded as follows: "0" for "female" and
"1" for "male." For age questions, respondents' age categories were
coded from 1 to 10 depending on their answers.[5] In terms of
education levels, the responses were coded as follows: "1" for "no
formal education," "2" for "primary school education," "3" for
"secondary school graduates," "4" for "polytechnic diploma holders,"
and "5" for "university graduates."[6]
Time spent weekly on the Web. For the measurement of Web use, the
respondents were asked to indicate how many hours or minutes they
spent on the Internet a week. Their answers, when in the form of
minutes, were converted to its equivalents in hours by dividing the
number of minutes by 60. A new variable was created to represent the
total time of weekly Web usage in terms of hours for all respondents.
Data Analysis
Hypothesis 1. The first hypothesis posits that the perceived effect
of the Web pornography on other adults will be greater than the
perceived effect on self. To test the hypothesis, the mean of
perceived negative effect from Web pornography on self is compared
with the mean of perceived negative effect from Web pornography on
other adults to see if the latter is indeed, as third-person effect
hypothesis posits, larger than the former. Secondly, a t-test is
performed to see if the perceived effect of Web pornography on self
is significantly different from the perceived effect of Web
pornography on other adults.
Hypothesis 2. The second hypothesis posits the size of third-person
effect will increase as the social distance of the comparison group
increases (i.e., when "others" change from "other adults" to "young
people"). To test the hypothesis, the means of perceived negative
effect from Web pornography on self, other adults and young people
are compared to see if when social distance between self and others
become wider, the perceived harmful effect will increase as well.
Secondly, a t-test was used to see if the perceptual bias about the
negative effect of Web pornography on self vs. other adults is
significantly different from the perceptual bias about the effect on
self vs. young people regarding the same issue. The t-test is
conducted to ensure if the enlarged third-person effect, if any, is
statistically significant.
Research Questions 1 and 2. The first research question asks the
extent to which the levels of public support for censoring Web
pornography are affected by perceived negative effects of the Web
pornography on oneself, other adults and young people. The second
research question inquires the extent to which the levels of public
support for censoring Web pornography are affected by factors such as
gender, age, education and Internet usage. To test the two research
questions, a regression analysis was performed, with the levels of
support for censoring Web pornography as the dependent variables, and
gender, age, education, Internet usage, negative effect of Web porn
on self, negative effect of Web pornography on other adults, and
negative effect of Web pornography on young people as the independent
variables.
Results
The sample of 710 adults in Singapore was 51.1% male, 71% married,
and 26.3% with tertiary education. The median age category was 35-39
years old, and the median monthly salary was in the range of US$1,801
to US$2,401. When compared with national census of Singapore
population (Singapore population, 2001), the demographics for the
sample used for the current study are very comparable.[7]
Hypothesis 1
The first hypothesis posits that the perceived effect of the Web
pornography on other adults will be greater than the perceived effect
on self. As shown in Table 1, the study found that the perceived
negative effect of Web pornography on other adults is greater than
the perceived negative effect of Web pornography on self. In
addition, according the results of t-test, the perceived negative
effect on other adults is significantly different from the perceived
effect on self. Based on this finding, the present study showed ample
support for the first hypothesis.
Table 1. Mean Scores of Perceived Effect of Web Pornography on Self
and Other Adults
(Standard Deviations in Parentheses)
N Self Other Adults Difference t-value
710 2.01 (1.13) 2.63 (1.03) .61 16.78***
Note: The responses were coded with a 4-point Likert scale, with "1"
as "not at all" and "4" as "a great deal." Significance level was
calculated using paired t-test.
*** p < .001
Hypothesis 2
The second hypothesis posits the size of third-person effect will
increase as the social distance of the comparison group increases
(i.e., when "others" change from "other adults" to "young people").
As shown in Table 2, while the perceived negative effect of Web
pornography on other adults was larger than the perceived effect of
Web pornography on self, the perceived effect of Web pornography on
young people is much greater than the perceived effect of Web
pornography on self. This finding provided a preliminary support for
hypothesis 2 because it showed the perceptual difference between self
and others changed as social distance between self and others widened
(i.e., the definitions of "others" changed from "other adults" to
"young people").
Table 2. Mean Scores of Perceived Effect of Web Pornography on
Self, Other Adults and
Young People (Standard Deviations in Parentheses)
N Self Other Adults Young People
710 2.01 (1.13) 2.63 (1.03) 3.42 (.85)
Note: The responses were coded with a 4-point Likert scale, with "1"
as "not at all" and "4" as "a great deal." Significance level was
calculated using paired t-test.
A more solid support of hypothesis 2 comes from findings illustrated
in Table 3. The figures in Table 3 showed that the perceptual bias
between self and young people regarding the negative effect of Web
pornography was not only larger than the perceptual bias between self
and other adults, but was also statistically different from the
latter. Specifically, the results of paired t-test revealed that the
difference between the self-young people perceptual bias and the
self-other adults perceptual bias was statistically significant (see
Table 3). This evidence provided ample support for hypothesis 2.
Table 3. Mean Scores of Perceptual Bias between Self and Other
Adults, and Perceptual
Bias between Self and Young People (Standard Deviations in Parentheses)
N Self & Other Adults Self & Young People Difference t-value
710 .61 (.98) 1.41 (1.22) .80 22.66***
Note: The perceptual bias between the perceived negative effect of
Web pornography on self and the perceived negative effect of Web
pornography on other adults was derived by subtracting the former
from the latter. Similarly, the perceptual bias between the
perceived negative effect of Web pornography on self and the
perceived negative effect of Web pornography on young people was
derived by subtracting the former from the latter. Significance level
was calculated using paired t-test.
*** p < .001
Research Questions 1 and 2
The first research question asks the extent to which the levels of
public support for censoring Web pornography are affected by
perceived negative effects of the Web pornography on oneself, other
adults and young people. The second research question inquires the
extent to which the levels of public support for censoring Web
pornography are affected by factors such as gender, age, education
and Internet usage. The two research questions were test using a
regression analysis, with the levels of support for censoring Web
pornography as the dependent variable, and gender, age, education,
Internet usage, negative effect of Web porn on self, negative effect
of Web porn on other adults, and negative effect of Web porn on young
people as the as the independent variables.
As shown in Table 4, the results of the regression analysis showed
gender, age, Internet use, negative effect of Web pornography on
self, negative effect of Web pornography on other adults, and
negative effect of Web pornography on young people were found to be
significant predictors of support for censorship of Web pornography.
The findings largely confirmed the previous findings about likely
predictors for censorship of undesirable media content (Chia et al.,
2004; Gunther, 1995; Gunther et al., 1996; Hoffner et al., 2002;
Hoffner et al., 1999; Lo et al., 2002; McLeod et al., 1997; Rojas et
al., 1996; Salwen, 1998; Salwen et al., 1997; Salwen et al., 1999; Wu
et al., 2001).
Examining the positive or negative sign of the significant predictors
reveals the relationship between the predictors and the dependent
variable (Schroeder, Sjoquist & Stephan, 1986). Among significant
predictors found through the test of the research
Table 4. Predictors for Support of Censorship of Web Pornography
Standardized
Coefficients
Gender -.13***
Age -.09*
Education -.01
Internet Use -.07+
Negative effect of Web pornography on self -.14**
Negative effect of Web pornography on other adults -.22***
Negative effect of Web pornography on young people -.14***
N = 710
Adjusted R Square = .21
*** p < .001; ** p < .01; * p < .05; + p < .10
questions, age, negative effect of Web pornography on self, negative
effect of Web porn on other adults, and negative effect of Web
pornography on young people have positive coefficients, revealing
their positive relationships with the dependent variable support for
censorship of Web pornography. For example, such positive
relationship in the case of age could mean that the older a person
is, the more likely he or she will support retractions on Internet
pornography. In contrast to the positive relationship, gender and
Internet usage have negative coefficients and therefore negative
relationship with the dependent variable. For example, a negative
relationship between Internet use and the dependent variable means
that the more a person uses the Internet, the less likely he or she
is going to support censorship of Web pornography. In a addition,
since gender is coded as a dummy variable with "0" representing
"female" and "1" representing "male," its negative relationship with
the dependent variable means women are more likely to support
restrictions on Web pornographic content.
Aside from reviewing the negative/positive relations between the
predictors and the dependent variable, examining the relative sizes
of the standardized coefficients also reveals the sizes of effects of
different significant predictors on the dependent variable
(Schroeder, Sjoquist & Stephan, 1986). Due to the relative size of
its coefficient, perceived negative effect of Web pornography on
other adults has the greatest influence on the dependent variable
support for censorship of Web pornography (see Table 4). Following
the same logic, perceived effect of Web pornography on young people
and perceived effect of Web pornography on self are next most
important predictors with equal sizes of regression coefficients,
followed by gender, age, and internet use.
In addition, as the third-person effect is reflecting the phenomenon
that the perceived negative media effect on others are greater than
the perceived negative effect on oneself, the present research was
aimed to test if perceived negative media effects on both types of
"others" (i.e., "other adults" and "young people") would be a
stronger predictors behind the support for censoring Web pornography,
compared to the perceived media effect on self. However, the findings
of the present showed that while perceived negative effect of Web
pornography on "other adults" is a stronger predictor than perceived
negative effect of Web pornography on "self," perceived negative
effect of Web pornography "young people" is not different from
perceived negative effect of Web pornography on "self." Judging from
the above findings, it seemed that the third-person effect affected
support for censorship of Web pornography when "others" are "other
adults" and did not affect support for censorship of Web pornography
when "others" are "young people."
Discussion
The present research tests two hypotheses and two research
questions. The first hypothesis posits that the perceived effect of
the Web pornography on other adults will be greater than the
perceived effect on self. The second hypothesis posits the size of
third-person effect will increase as the social distance of the
comparison group increases (i.e., when "others" change from "other
adults" to "young people"). The first research question asks the
extent to which the levels of public support for censoring Web
pornography are affected by perceived negative effects of the Web
pornography on oneself, other adults and young people. The second
research question inquires the extent to which the levels of public
support for censoring Web pornography are affected by factors such as
gender, age, education and Internet usage.
The present study provided ample support for the hypotheses,
confirming both the existence of the third-person effect and the
social distance corollary (i.e., the greater the social distance
between self and others, the larger the third-person effect) in the
context of public attitudes about the negative effect of Web
pornography in Singapore. In addition, the testing of the research
questions showed gender, age, Internet usage, perceived negative
effects of the Web pornography on oneself, perceived negative effects
of the Web pornography on other adults, and perceived negative
effects of the Web pornography on young people are all significant
predictors of the public support for censorship of Web pornography in
Singapore. Findings of the current study are very interesting because
it largely confirmed previous empirical evidence about the
third-person effect and the influence of the effect and other factors
behind the support for censorship of Web pornography. In addition,
the research also measures the general public's attitudes toward the
third-person effect and factors behind support for censorship measure
in Web pornography. The findings apparently have implications for
policymakers regarding the issues of Web pornography censorship.
Specifically, the present study confirmed empirical evidence in
previous research supporting the existence of third-person effect in
the context of undesirable media content (Perloff, 1999). The
findings of the current research showed that the public perceived Web
pornography as having greater negative effect on other adults than on
themselves. In addition, the present study also supported past
findings on the social distance corollary (Chia et al., 2004; Cohen,
Mutz, Price & Gunther, 1988; Duck, Hogg & Terry, 1995; Gibbon &
Durkin, 1995; Gunther, 1991; McLeod et al., 1997; Lo et al., 2002;
White, 1997). Similar to previous findings, the present study lends
further support to the hypothesis that the wider social distance
between self and others, the larger the third-person effect. Findings
showed that when the "others" changed from "other adults" to "young
people," the perceived negative effect of Web pornography on others increased.
Besides confirming third-person effect and the social distance
corollary, the present study also support past research findings
regarding predictors behind the support for censorship of undesirable
media content. Specifically, past research showed third-person
effect, or perceptual bias regarding negative effect of undesirable
media messages on self vs. others, contributed to the support for
censorship of such media content (Gunther, 1995; Gunther et al.,
1996; Hoffner et al., 2002; Hoffner et al., 1999; McLeod et al.,
1997; Rojas et al., 1996; Salwen, 1998; Salwen et al., 1999; Wu et
al., 2001). As the third-person effect is really reflecting the
phenomenon that the perceived negative media effect on others are
greater than the perceived negative effect on oneself, the present
research test if perceived negative media effect on "others" would be
a stronger predictor behind the support for censoring Web
pornography, compared to the perceived media effect on self. As the
potentially harmful media content tested in the current study is Web
pornography, perceived effect of Web pornography on self and
perceived effect of Web pornography on two groups of "others" (i.e.,
other adults in Singapore and young people in Singapore) was tested
as predictors for public support to censor Web pornographic content.
In other words, perceived negative effect of Web pornography on other
adults, perceived negative effect of Web pornography on young people,
and perceived negative effect of Web pornography on self were all
tested as predictors of support for censorship of Web pornography.
And if third-person effect does influence support for censorship of
Web pornography, the negative effects of Web pornography on both
other adults and young people will be stronger predictors of Web
pornography censorship support than the negative effect of Web
pornography on self. As predicted, the results of the current study
showed that the perceived negative effect of Web pornography on other
adults is a stronger predictor than the perceived negative effect of
Web pornography on self, judging from their relative sizes of
regression coefficients on the dependent variable support for
censorship of Web pornography (see Table 4). However, the findings
did not show any major difference in the size of regression
coefficients for both the negative effect of Web pornography on young
people and the negative effect of Web pornography on self (see Table
4). Judging from the above findings, it seemed that the third-person
effect affected support for censorship of Web pornography when
"others" are "other adults" and did not affect support for censorship
of Web pornography when "others" are "young people." This finding is
very intriguing for two reasons: (1) there is an apparent greater
third-person effect when "others" are "young people" rather than
"other adults" (see Tables 2 and 3); and (2) the greater third-person
effect – meaning greater concern for possible harm to "young people"
– did not translate into support for censorship of Web pornography.
Put it another way, it seemed that the respondents believed young
people are more vulnerable to the negative effect of Web pornography
than other adults, but their support for the censorship of Web
pornography seemed to be based more on the negative effect of Web
pornography on other adults than the negative effect Web pornography
on young people. One possible explanation of this phenomenon may be
that even though adults believe young people in Singapore are
vulnerable to negative effect of Web pornography, the youngsters,
however, may not have as much access to Web pornography as is the
case of other adults. It is possible that due to strong family ties
in Singaporean families, parents can effectively prevent young people
from accessing pornographic Web content.
Besides the third-person effect, demographic variables (i.e.,
gender, age and education) and Internet usage are also investigated
in the present study for their possible influences in the levels of
public support for the censorship of Web pornography. The results
showed gender, age and Internet usage are significant predictors of
the public support for censorship of Web pornography (see Table 4).
Education, on the other hand, was not found to be a significant
predictor of such censorship measure. The findings mostly confirmed
past empirical evidence. For example, the findings that women are
more likely than men to support censorship of Web pornography are
consistent with previous findings (Gunther, 1995; Gunther et al.,
1996; Hoffner et al., 1999; Lo et al., 2002; Rojas et al., 1996).
Similarly, the findings that more exposure to the Internet tend to
lower support for censorship of Web pornography also match the
researcher's prediction made based on a synthesis of past research on
the link between media use and support for censorship measure (Chia
et al., 2004; Gunther, 1995; Hoffner et al., 1999; Lo et al., 2002;
Salwen et al., 1997; Wu et al., 2001). Although education was not
found to be a predictor of support for censorship of Web pornography,
it is not an inconceivable finding. In a society like Singapore that
prides itself with high Internet penetration (Iritani, 2000), it is
likely the majority of the public are well aware of the potential
harms of Web pornography, regardless of their educational backgrounds.
Besides confirming past research findings, another contribution of
the current research is the fact it is a large-scale survey seeking
to use third-person effect and other factors (such as demographics
and Internet usage) to explain the levels of public support for
censorship of Web pornography. Previous studies on the link between
third-person effect and the support for censorship of pornographic
media content seemed to either focus on non-Internet pornographic
content (Gunther, 1995; Gunther et al., 1996; Hoffner et al., 2002;
Hoffner et al., 1999; McLeod et al., 1997; Rojas et al., 1996;
Salwen, 1998; Salwen et al., 1999), or surveyed student populations
for the link between third-person effect and support of censoring Web
pornography (Lo et al., 2002; Wu et al., 2001). The present study
thus provides more evidence about the general public's attitudes
toward how third-person effect and other factors (such as gender,
age, and Internet usage) affect the levels of the support for
censorship of Web pornography.
As the present study is a large-scale survey on the public opinions,
its implications for policy makers may be quite useful. First of all,
the survey found that women, older people, and infrequent Internet
users are more likely to support censorship measures against Web
pornographic content. Given this finding, policymakers will know
where their support base will come from if they need to establish or
strengthen restrictions on public access to Web pornography.
Secondly, as findings from the current study showed that the
perceived negative impact of Web pornography on other adults, rather
than the perceived impact on self or young people, is the biggest
reason why people support censorship of Web pornography in Singapore,
it may be a sign suggesting access to pornography is more prevalent
among adults than among young people. This may be vital information
for policymakers in the country.
Limitations of the study include the exclusion from the sample
non-residents in Singapore. Although Singapore citizens and permanent
residents currently comprise more than 80% of the population[8] and
the present sample on them should be sufficient to reflect public
opinion in the country, inclusion of the non-residents, however, will
provide a more complete picture of the issues investigated. Another
limitation of the current study is the measurement of media use.
Although using weekly time spent on the Web should be a good measure
of media use, a more precise measure of the media use would be the
respondents' exposure to Web pornographic materials.
Still, the present research is very interesting and useful. The
study confirmed past empirical evidence about the existence of
third-person effect and social distance corollary. In addition, its
findings on the influence of third-person effect and other factors
(such as gender, age and Internet usage) on the levels of public
support for censorship of Web pornography should be useful to
policymakers. At a time when more and more people are surfing the
Net, the current study will help to add to the understanding of some
of the public attitudes toward the use of the young and developing media.
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[1] Notes:
The Website that provides the information, Internet World Stats,
reported that the Internet usage information comes from data
published by Nielsen//NetRatings, by International Telecommunications
Union, by NICs and other reliable sources.
[2]
Two published studies about reasons behind the support for
censoring Web pornography based their findings on responses from high
school and university students (Lo & Wei, 2002; Wu & Koo, 2001),
rather than from of the large-scale general public. For example, Wu
and Koo (2001) surveyed a group of students at a university in
Singapore to explore factors behind the support for censorship of Web
pornography. Similarly, Lo and Wei (2002) polled high school and
university students in Taiwan on reasons behind their levels of
support for censoring Web pornography. The present study targets at a
different population – the general public – to see their levels of
support for the censorship of Web pornography.
[3] The respondents are either Singaporeans or Singaporean permanent
residents. They do not include non-residents in Singapore. According
to census figures by the Singapore government, non-residents in
Singapore comprise of 19.7% of Singapore's total population of 4.13
million in 2001 (source: Statistics Singapore Newsletter [url:
http://www.singstat.gov.sg/ssn/feat/nov2003/pg10-13.pdf] released in
September 2003).
[4] In an effort to encourage responses to the age question, the
respondents were asked to indicate their age categories, instead of
the actual age. The age categories were coded as follows: "1" for
"18-24 years old," "2" for "25-29 years old," "3" for "30-34 years
old," "4" for "35-39 years old," "5" for "40-44 years old," "6" for
"45-49 years old," "7" for "50-54 years old," "8" for "55-59 years
old," "9" for "60-64 years old," and "10" for "65 years old and older."
[5] See endnote No. 4.
[6] The list of coding option for the variable of education (i.e.,
no formal education, primary school education, secondary school
graduates, polytechnic diploma holders, and university graduates) was
derived thru conversion from the original response options: no formal
education, primary 6 or less, some secondary, "O" level, "A" level,
diploma, and degree & above. The conversion is designed to translate
the educational qualifications to easier-to-understand terms to
facilitate the interpretation of research analysis.
[7] The demographic statistics of the sample for the current study
(n = 710) is very comparable with the population parameters obtained
during the census in 2000 (Singapore population, 2001):
* The census figures for various demographic categories are for
Singapore citizens and permanent residents. As in the case of the
current sample, the demographic figures provided for the census do
not cover records for non-residents in Singapore.
** The records with a "**" sign are for those aged 15 and over; the
records without a "**" sign are about people of all ages.
*** Tertiary education includes polytechnic diploma holders and
university degree holders.
**** The figures are converted from original Singapore dollar figures.
[8] See endnote 3.
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