Journal of Information Technology & Politics, 7:22–35, 2010
Copyright © Taylor & Francis Group, LLC
ISSN: 1933-1681 print/1933-169X online
DOI: 10.1080/19331680903109402
From the Digital Divide to the Democratic Divide: Internet
Skills, Political Interest, and the Second-Level Digital
Divide in Political Internet Use
WITP
Seong-Jae Min
Min
ABSTRACT. Digital divide research is now focused on the so-called second-level divide, which
concerns Internet “usage” divides. This article suggests that while the first-level divide was associated
with sociodemographic factors, the second-level divide is associated with factors such as motivations
and Internet skills. It then illustrates an example of the second-level digital divide—the democratic
divide. The democratic divide concerns the differences between those who actively use the Web for
politics and those who do not. Analysis of General Social Survey data shows there is a democratic
divide where political Internet users are individuals with high Internet skills and political interest.
KEYWORDS. Democratic divide, digital divide, e-democracy, Internet politics, Internet skills,
second-level divide
disadvantages for the already marginalized
groups in society. With the persistence of the
digital divide, will the old, the poor, and other
social minorities who lack access to ICTs fall
behind in their ability to exploit the many
opportunities brought about by the digital
revolution?
The present study proposes that the digital
divide will not likely disappear. It is argued that
the current Internet access divide will persist in
the form of “usage” divides. One of the Internet
usage divides explored in this study is what
Norris (2001) called the “democratic divide,”
which concerns people’s differential usage of
the Internet for political purposes. The democratic divide, if any, raises a critical social question since it suggests that there may be
There is a concern that information and communication technologies (ICTs), which are
expected to contribute to the development of all
humans, actually widen the inequalities
between the developed world and the underdeveloped world, the rich and poor, whites and
blacks, the educated and less-educated, etc.,
creating the so-called “digital divide” (Van
Dijk, 2005; Warschauer, 2003).1 Some studies
have shown that access to ICTs is unequal
along lines of socioeconomic status, gender,
age, race, and geography (e.g., Mossberger,
Tolbert, & Gilbert, 2006; National Telecommunications and Information Administration
[NTIA], 1995, 1999, 2000). The digital divide
raises an important social question, because
unequal access to ICTs may cause additional
Seong-Jae Min is Assistant Professor of Communication Studies at Pace University in New York City.
His research focuses on political communication, new technologies, and deliberative democracy. This
research was supported by the Survey Research Fellowship program at The Ohio State University’s College
of Social and Behavioral Sciences, where the author received his Ph.D. degree.
Address correspondence to: Seong-Jae Min, Department of Communication Studies, 5th floor, 41 Park
Row, New York, NY 10038 (E-mail: sjminn@yahoo.com).
22
Min
politically marginalized people in the digital
world. If the Internet, which is much touted as a
democracy-promoting medium, is mainly used
by a certain segment of the population, then its
democratic potential will be greatly undermined. This study explores the existence of the
democratic divide, and in so doing, it seeks to
identify what types of social and individual
factors cause the divide.
DIGITAL DIVIDE: IS THERE
AN ISSUE?
Despite the concern about the digital divide,
some analysts deny either the existence or the
severity of the phenomenon (see, e.g., Compaine,
1988, 2001; NTIA, 2004; Thierer, 2000). Their
main argument is that the digital divide will
eventually disappear, as have other technological divides in history. Compaine (1988, 2001)
argues that technological gaps or divides
among people would hardly occur, because, as
the world’s workforce becomes wealthier and
as technology costs decline, differences in all
aspects of living standards decrease. Compaine
cites the history of various technologies (e.g.,
electricity, radio, telephone, and automobiles)
that were innovations in the past century and
have followed a similar developmental path.
This path involved starting on a small scale at a
high price and use only by wealthier people.
However, as the volume of use increased, the
cost of providing the product decreased, allowing use of the new technology to diffuse rapidly
through society, thus removing the gap. Like
Compaine, Thierer (2000) makes a claim that it
is premature to act to defeat the digital divide,
because society needs time to see how the technology will adjust itself to the natural market.
Thierer thus suggests that government involvement in the digital divide issue will not be
necessary; if any intervention is required, it
would be to remove tax and regulatory roadblocks that discourage companies in the free
market from offering consumers the new products and services that they demand.
If one accepts the argument by Compaine
(1988, 2001) and Thierer (2000), then it is not
necessary to worry about the digital divide. The
23
divide will eventually fade away as ICTs
become more pervasive and inexpensive. However, there are many reasons to believe that the
digital divide will persist or even widen in the
future. First, their analogy between the diffusion
of ICTs and the diffusion of other technologies,
such as the automobile or telephone, fails.
ICTs, especially computer and Internet technologies, are different from other technologies in
that they are much more complex, multifunctional, and are considered to be “platform”
technologies for information and knowledge
(Van Dijk, 1999; Van Dijk & Hacker, 2003).
Unlike users of radios, television, and automobiles, users of computers and the Internet must
actively upgrade the hardware, software, and
individual skills to use them. ICTs become outdated much faster than any other technologies,
and users always have to catch up with the latest
technologies so as to not lag behind. For example,
users must keep upgrading software and Internet connection speeds to remain productive.
Furthermore, the Internet is different from other
technologies in terms of the amount of information and knowledge it generates. Facing information and knowledge that increase every
second, Internet users are asked to constantly
improve critical skills, such as the ability to
search, select, process, and apply information
from a superabundance of sources (Van Dijk &
Hacker, 2003, p. 316).
This suggests it is possible that those who
have been exposed to computers and the Internet
from the earliest stages are better situated in the
current information society, because they have
already gathered a lot of information and
knowledge and can use these tools to find additional resources and to upgrade the skills
required maintain their productivity. In other
words, unlike users of traditional media, ICT
users will likely have much different levels of
efficiency and experience in using the new
technologies. This observation, in essence,
represents the heart of the knowledge gap
hypothesis (Tichenor, Donohue, & Olien, 1970)
and the “Sesame Street effect” (Cook, Appleton,
Conner, Shaffer, Tamkin, & Weber, 1975),
which asserts that, even when everyone has
equal access to media and technologies, the
information gap between the haves and have-nots
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will not decrease because the haves typically
make better use of media and technologies. For
example, in studying the Sesame Street effect,
researchers showed that children with a higher
socioeconomic status achieve more educationally
than children with a lower socioeconomic
status, despite similar educational settings
(Attewell & Battle, 1999). Similarly, diffusion
theorists (Rogers, 1995; Ryan & Gross, 1943)
showed that, without successful policy initiatives, the existing differences in socioeconomic
status may structure the diffusion of technological
innovations. According to Rogers, early adopters
of technological innovations, when compared
with laggards, had a higher socioeconomic status.
An important point of Rogers’ theory is that the
adoption of successful new technologies often
reinforces the existing socioeconomic status;
thus, the rich get richer, and the poor remain
poor or even become poorer.
While Compaine (1988, 2001) and Thierer
(2000) predict that the diffusion of ICTs will
gradually become normalized over time, as
other technologies historically have, Rogers
(1995) argues that diffusion of innovations is
often structured by the social environment surrounding the technologies. At which end of the
spectrum—between normal diffusion and structured diffusion—will ICTs be placed? Considering the intrinsic characteristics of ICTs—that
they are complex, fast-evolving, and information
generating—they are more likely to be placed
at Rogers’ end. This notion has actually been
supported by some empirical research (Atkin &
Jeffres, 1998; Lin, 1998). For instance, Atkin
and Jeffres showed that the early Internet
adopters’ profiles roughly matched with those
predicted by Rogers’ diffusion theory.
THE SECOND-LEVEL DIGITAL
DIVIDE
The argument by Compaine (1988, 2001)
and Thierer (2000) stems from their conceptualizations of the digital divide solely in terms of
“access” to ICTs; under such a definition of the
digital divide, they may be correct. As computers
and the Internet become more and more widespread in society, it is possible that the access
divide to ICTs may eventually disappear.
Indeed, as of 2008, the Internet penetration rate
in the United States is as high as 74 percent
(Pew Internet and American Life Project,
2008), and the figure will continue to increase
to include an even larger population. However,
Compaine and Thierer fail to acknowledge that
the digital divide is a much more complicated
and multifaceted phenomenon that goes beyond
the mere issue of access.
Recent research has focused on what some
have termed the “second-level” digital divide
(Hargittai, 2002a, 2002b), which is a divide that
concerns “multiple layers of access and use” of
ICTs (Norris, 2001; Van Dijk, 1999). The
results of such research suggests that individuals
have diverse ways of accessing and using ICTs
and that these multiple layers of access and use
are often determined by a variety of factors that
include not only socioeconomic and demographic elements, but also physical, psychological,
cultural, and ecological factors. Hargittai
emphasizes that what matters in the study of the
digital divide is the user’s skill level in using
ICTs. She demonstrated that there is a skill
divide among Internet users, in that highly
skilled users make better use of the Internet.
Others (Adams, Stubbs, & Woods, 2005; Stanley,
2003) have focused on psychological variables
of individuals and have demonstrated that there
are individual psychological differences motivating the access to and use of ICTs. From an
ecological perspective, Ball-Rokeach’s Metamorphosis Project and its Internet Connectedness Index (ICI) also address the aspects of
multifaceted Internet use (Jung, Qiu, & Kim,
2001; Matei & Ball-Rokeach, 2003). The ICI
attempts to capture the scope and centrality of
Internet incorporation into people’s everyday
lives, rather than identifying simple access
divide.
Selwyn (2004) suggests that researchers
should approach the issue of the digital divide
more comprehensively; accordingly, one
should consider the dimensions of “access,”
“use,” and “consequences.” Access to ICTs
does not simply mean the binary distinction of
whether the population has ICT access or not.
The issue involves both the quality of access,
including speed, as well as the ease of access.
Min
In the use dimension, how people make use of
ICTs and what factors influence the different
uses will have to be investigated. Finally, Selwyn
argues that we need to examine the consequences of engaging meaningfully with ICTs,
studying the impact of the use of ICTs on the
various dimensions of citizens’ participation in
society. Similarly, DiMaggio and Hargittai
(2001) suggest five dimensions along which the
digital divide may exist: “technical means” that
concern software, hardware, and connectivity
quality; “autonomy of use” that concerns the
location and quality of access; “use patterns”
that concern the types of Internet use; “social
support networks” that concern the availability
of others one can turn to for assistance with use
of ICTs; and “skills” that involve one’s ability
to use the medium effectively. These researchers provide a useful analytical framework, one
that guides the present study to investigate the
complicated phenomenon of the digital divide
at the “second” level.
THE DEMOCRATIC DIVIDE
Following the theoretical framework developed by recent digital divide researchers, as
described above, this study attempts to look at
the multifaceted aspects of the digital divide
beyond the simple issue of access. Of particular
interest is the probing of individuals’ different
usage patterns of the Internet, because as the
Internet spreads widely, what matters is not
access to the Internet, but how people actually
use it. In particular, the study focuses on individuals’ “political” use of the Internet due to
the medium’s ever-increasing importance for
political participation.
One area where the Internet is bringing new
kinds of social interaction is the realm of politics. The Internet at present is characterized as
being, among other things, multimodal, interactive, horizontal, low-cost, and nonterritorial.
These characteristics may provide high hopes
for the future of democracy. Hence, Internet
enthusiasts have argued that the Internet can
contribute to democracy by bonding people,
regardless of territory, and by creating public
spheres and new social movements (Rheingold,
25
1993; Schwartz, 1996). Many studies (e.g., Hill
& Sen, 2005; Ott & Rosser, 2000) have shown
how citizens use computers and the Internet for
enhanced political and democratic initiatives.
For the so-called cyber pessimists, however, the
Internet is a digital replica of the real world
where one observes politics as usual (Margolis
& Resnick, 2000; Wilhelm, 2000).
Norris (2001) adds to the discussion of Internet
politics by proposing the democratic divide
hypothesis. She suggests that the democratic
divide signifies “the differences between those
who do, and do not, use the panoply of digital
resources to engage, mobilize, and participate
in public life” (p. 4). The existence of the democratic divide, to any extent, poses an important
social question. Under the concept of the democratic divide, according to Norris, the Internet
mainly serves to reinforce the activism of the
activists, facilitating participation for those who
are already interested in politics; whereas those
who are disengaged from the politics of the real
world may further lag behind in the digital
world. A similar concern was raised, with
empirical support, when Shelley, Thrane, and
Shulman (2006) investigated generational differences in Internet use. They argued:
By permitting some citizens to conduct
their routine business with the government more easily, information technology
appears to be widening the gap between
the IT literate and those without basic
navigation skills. As society becomes
increasingly dependent on e-government,
social barriers will be compounded if
non-electronic voices are marginalized
from political participation. (p. 48)
As such, the issue of the democratic divide provides an important caveat for the future of
e-democracy.
The democratic divide explained here is a
rather broad concept that concerns many
aspects of digital civic life. As mentioned in the
previous section that Selwyn (2004) suggests,
the democratic divide may occur along the lines
of ICT access, use, and consequence. In the
present study, however, the democratic divide
will be defined operationally as “the divide
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JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
pertaining to individuals’ differential use of the
Internet for politics.” This is because the “use”
dimension is perhaps the most noticeable aspect
of the democratic divide that easily warrants
empirical investigation, and the Internet is the
representative medium of all ICTs today.
SKILLS, MOTIVATIONS, AND
POLITICAL INTERNET USE
If there is a divide in individuals’ Internet
use for politics, what would drive such a
divide? Conventional studies typically associate
socioeconomic and demographic factors with
the divide. Previous empirical studies have
shown that those who are active in Internet
civic engagements are usually people with
higher socioeconomic status (Hill & Hughes,
1998; Norris, 1999). In those studies, basic
demographic and socioeconomic factors such
as gender, age, educational level, income, and
race were considered to be major determinants
of differential Internet use for politics. Specifically, the studies demonstrated that males,
whites, and those with higher education and
income are more likely to be active in using the
Internet for political affairs.
In addition to basic demographic and socioeconomic factors, however, factors such as individuals’ Internet skills and political motivations
should matter as well. Indeed, skills and motivations may be the two most important factors
that would explain individuals’ differential Internet use for politics. As the Internet becomes
more and more widespread in society and as new
political opportunities available online increase,
the importance of Internet skills and political
interest will matter even more, if one wants to
use the Internet meaningfully for political purposes. At the same time, we may observe a
decrease in the importance of socioeconomic
and demographic factors as the Internet is more
and more evenly accessed and used across the
population.
Internet skills, or Internet literacy, have
received some attention in recent years. As Hargittai (2002b, 2005) argues, individuals’ online
behavior is, in part, a reflection of their online
skills. This makes sense because without relevant
skill levels and knowledge of the Internet, it
would be difficult for citizens to engage in such
digital political initiatives as online donation,
signing electronic petitions, and discussing politics online. Internet skills have several dimensions and can be measured by behavioral and
self-reported measurements (Hargittai, 2005).
These include knowledge of and experience
with the medium, practical ability, and confidence in using it. The level of Internet skills
may be related to schooling, because people
with higher levels of education are likely to
have had more exposure to the Internet for
educational purposes. Yet formal schooling
does not necessarily guarantee good Internet
skills, because Internet skills also include many
practical Internet abilities used in everyday life.
Therefore, good Internet skills, independent of
level of education, may serve as a predictor of
online political actions.
Motivations, or interest, are another important
factor that may predict citizens’ online political
engagements. As Norris (2001) points out, the
Internet is a medium of par excellence and a la
carte. That is, Internet users tend to select and
customize information for their own interests.
People determine which emails they respond to
and which listservs they join. In this way,
according to Norris, those who have high political
interests and motivation are more likely to
engage in public activities that are available
online, thereby enhancing the scope of their
political influence. This argument is in line with
the famous uses and gratifications approach in
media studies, which avers that people use
media in ways that will satisfy their needs and
interests. Due to its high potential for customization, the Internet provides many good opportunities to satisfy specific individual interests.
Katz and Rice’s (2002) extensive empirical
study suggests that people use the Internet
differently so that it fits with the important
aspects of their lives.
Thus, Internet skills and political interest are
key factors that may cause the democratic
divide, especially when it concerns the political
use of the Internet. In a classic study of traditional
political participation such as voting and community engagements, Verba, Schlozman, and
Brady (1995) showed that capacity and motivation
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matter in determining the level of participation.
This observation may hold true in the online
environment as well: not just the simple existence
of new technology, but human interest and
skills, will lead to meaningful political participation using the technology. Therefore, in addition
to basic demographic and socioeconomic factors, this study analyzes the role of political
interest and Internet skills in the use of the
Internet for politics.
HYPOTHESES AND RESEARCH
QUESTIONS
This section formulates some hypotheses and
research questions based on the rationale presented thus far. First, as suggested in the
review, it is likely that there is a democratic
divide in cyberspace such that individuals
differentially use the Internet for politics. Who
uses the Internet for politics and who does not?
This question should be addressed first. Therefore,
RQ1: What are the profiles of Internet users
for politics?
Second, it has been argued that Internet skills
and political interest are key factors that predict
differential Internet use for politics, because
political Internet use requires a certain level of
Internet skills and political motivations. Therefore,
H1: Internet skills will be positively associated with political Internet use.
H2: Political interest will be positively associated with political Internet use.
27
Kim, Koch, & Park, 2006). Although it is a few
years old, the 2004 GSS contains extensive
questions on Americans’ political behavior,
attitudes, and Internet use. In particular, the
2004 GSS contains a special Information Society
topical module that allows detailed assessment
of the respondents’ Internet skills and political
Internet use patterns. Because of these advantages, the 2004 GSS was adopted for in-depth
empirical investigation.
The GSS is a face-to-face, full-probability
sample survey of adults living in households in
the United States. The 2004 GSS had a
response rate of 70.4 percent out of a 3,628 person net sample. For the analysis of Internet use
divide, only the Information Society module
was selected. This yielded a subsample of 684
adults who said they used the Internet.
Measurements
Political Internet Use
This was the dependent variable, which
operationally represented the concept of the
democratic divide. Political Internet use consisted of two dimensions: online political information seeking and online political discussion.
Online political information seeking was a
dichotomous variable, where those who said
they visited a political Web site in the past month
were coded 1 and those who said they had not
were coded 0 (variable POL30 in the GSS questionnaire. For actual wording, see Appendix).
Online political discussion (INTERPOL) was also
a dichotomous variable, where those who joined
online political discussion were re-coded 1.
Internet Skills
METHOD
The Dataset
The main goal of this study is to look at the
existence of the democratic divide in terms of
Internet use among individuals. To this end, the
2004 General Social Survey (GSS) dataset was
analyzed. The GSS is perhaps one of the most
authoritative datasets in social science survey
research today and has been considered representative and methodologically rigorous (Smith,
The GSS dataset had comprehensive measures
of Internet skills. These included self-reported
ability to use the Web, knowledge of Internet
terms, and practical knowledge of how to
exchange files using the Internet. A composite,
general Internet skills index was constructed
considering the three dimensions above: selfreported Web ability, knowledge of Internet
terms, and practical skill. Self-reported Web
ability in the dataset (WEBABLE) was reversecoded so that it could range from “very poor” to
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JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
“excellent” (M = 3.88, SD = .98 on a five-point
scale of 1 to 5). The knowledge score variable
was built from the three questions (ADVSRCH/
PREFSETS/NEWSGRPS) that measured the
respondents’ familiarity with Internet terms.
Respondents who said they were either “very
familiar” or “somewhat familiar” with the three
terms “Newsgroups,” “Advanced Search,” and
“Preference Settings” received three points.
Respondents received two points for familiarity
with two terms, one point for one term, and 0
points for no familiarity with any of the terms
(M = 2.13, SD = 1.03 on a four-point scale of 0
to 3). Practical skill was measured by the variable
(UPLOAD/DOWNLOAD),
which
asked
whether the respondents knew how to upload
and download files using the Internet. Respondents received two points if they knew how to
both upload and download files, one point if they
knew how to either upload or download, and 0
points for no practical skill of file exchange (M =
1.54, SD = .76 on a three-point scale of 0 to 2).
Each of the three skill scores—self-reported skill,
knowledge, and practical skill—was standardized
and then added together to make a composite
index (Cronbach’s a = .81, M = 7.55, SD = 2.37
on a ten-point scale of 1 to 10).
Political Interest
The 2004 GSS had a standard political interest
item (POLINT1) that asked the respondents how
much they were interested in politics. The
responses were reverse-coded so that a higher
number meant higher interest (1 meant “not interested at all” and 4 meant “very interested.” M =
2.86, SD = .82 on a four-point scale of 1 to 4).
Socioeconomic and Demographic
Variables
Previous research (e.g., Norris, 1999) suggests that individuals’ Internet use for politics
may be different based on gender, income, education, age, and race. Therefore, these variables
were used as independent variables. Gender
was coded with female being 0 and male being
1 (57.7 percent females). Education, measured
as the highest year of school completed, was
used as a continuous variable (M = 14.56, SD =
2.57). Total household income was measured
on a 23-point level, ranging from less than
$1,000 to more than $110,000. The median
income fell between $50,000 and $59,999.
Income was also used as a continuous variable.
Age was used as a continuous variable (M =
42.69, SD = 14.48). Race was reorganized into
a dichotomous variable: Whites and Asian
Americans were coded 0 and African Americans, Hispanics, and other races were coded 1.
The rationale for this rather unorthodox coding
was that previous research shows that whites
and Asian Americans tend to have a high level
of Internet access and use, whereas African
Americans’ and Hispanics’ access and use fall
much behind those of whites and Asian Americans (NTIA, 1995, 1999, 2000). In other words,
whites and Asians can be regarded as a majority, whereas other races can be considered a
minority in terms of Internet use.
Analytic Strategy
To probe individuals’ differential Internet
use for politics, first of all, the profiles of political versus nonpolitical Internet users were
descriptively analyzed based on socioeconomic and demographic factors. Second, to
make a statistical inference to the larger American Internet population, a logistic regression
analysis was performed. Here the dependent
variables were two: online political information
seeking and online political discussion. The
independent variables were socioeconomic and
demographic variables, Internet skills, and
political interest.
Lastly, a structural equation model was constructed to further assess the effects among the
variables. One of the advantages of using structural equation modeling here was that it could
increase the reliability of the measurement. For
example, the Internet skills variable in this
study had three dimensions, and it would have
been difficult to find out in conventional regression analysis whether these three would reliably
represent the Internet skills variable. In the
structural equation model, however, the three
were not simply added together, but were
regarded as multiple indicators of a latent variable. This also held true to the political Internet
use variable, which had two dimensions. This
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type of analysis allows for assessment of the
coefficients between the indicators and their
corresponding latent variable with measurement errors, which can contribute to the reliability of the measurement.
In the structural equation model, socioeconomic and demographic variables, Internet
skills, and political interest were used as exogenous variables. The Internet skills variable was
constructed as a latent exogenous variable that
was measured by the three observed variables
(dimensions) of self-reported skill, knowledge,
and practical skill. Political interest, gender,
race, income, education, and age each involved
a single observed variable. Political Internet use
was the latent endogenous variable measured
by the two observed variables of online political information-seeking and online political
discussion.
Some of the observed variables in the structural equation model were ordinal or categorical in nature. Methodologists suggest correction
for estimation involving ordinal or categorical
variables in structural equation modeling. This
is because, for categorical and ordinal variables,
the assumptions of multivariate normality are
not met when using distribution-dependent
methods, such as the maximum likelihood
(ML) estimator (Mueller, 1997). Therefore,
methodologists recommend using the weighted
least squares (WLS) method, which is based on
the polychoric correlation matrix for estimation
involving ordinal and categorical variables
(Bollen, 1989). Following their suggestion,
polychoric correlations of the variables were
entered into LISREL 8.8, and the parameters
were estimated using the WLS method.
RESULTS
The first research question concerned probing the profiles of political and nonpolitical
Internet users. Of the 684 Internet users in the
GSS dataset, 295 (around 43 percent) were
political Internet users. These were the people
who said they had ever visited a political Web
site or joined a political discussion group. The
cross-tabulation results in the third and fourth
columns of Table 1 show that compared with
29
nonpolitical users, political users of the Internet
in this sample tended to be male, highly educated, and have high income: there were more
females (63.4 percent) than males (36.6 percent) among nonpolitical Internet users; of all
political Internet users, 49.0 percent had at least
college degrees, whereas only 33.2 percent of
nonpolitical Internet users had college or higher
degrees; of political Internet users, 38.0 percent
had a family income of $75,000 or higher,
whereas only 27.1 percent of nonpolitical Internet users had an income of $75,000 or higher.
Pearson chi-square tests suggest that the differences in political Internet use were statistically
significant along the lines of gender (c2 =
11.28, df = 1, p < .01), education (c2 = 25.98,
df = 4, p < .001), and income (c2 = 12.90, df = 2,
p < .01).
To make a statistical inference to the larger
American Internet population, a binary logistic
regression analysis was performed for political
Internet users in the GSS sample. In a series of
binary logistic regression analyses, the independent variables were regressed upon the dependent variables, online political information
seeking and online political discussion. Table 2
summarizes the two logistic regression results.
According to Table 2, the respondents’ gender,
income, political interest, and Internet skills
were statistically significant predictors of
online political information-seeking; that is,
males with high income, high political interest,
and good skills were associated with greater
probability of using the Internet for political
information. For the predictors of online political discussion, only Internet skills and political
interest were statistically significant; that is,
each one unit increase in Internet skills and/or
political interest was associated with greater
probability of using the Internet for political
discussion. Hypotheses 2 and 3 were supported.
The structural equation model with path
coefficients and standard errors is presented in
Figure 1. This model also supported the hypotheses and corroborated the findings of the logistic regression analysis. According to the model,
Internet skills (g = .63, p < .001, unstandardized
coefficient) and political interest (g = .42, p <
.001, unstandardized coefficient) were strong
predictors of Internet use for politics. Furthermore,
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TABLE 1. Demographic and Socioeconomic Profiles of Internet Users, Political
Internet Users, and Nonpolitical Internet Users (%): General Social Survey, 2004
Total Internet users
(n = 684)
Gender**
Male
Female
Race
White
Black
Asian
Hispanic
Age
18–29
30–49
50–64
Over 65
Education***
Less than high school
High school graduates
Some college
College graduates
Advanced degrees
Income**
Low (Under $40,000)
Middle ($40,000–74,999)
High (Over $75,000)
Political Internet users
(n = 295)
Nonpolitical Internet users
(n = 383)
42.3
57.7
49.3
50.7
36.6
63.4
81.5
11.4
2.9
2.6
82.5
10.6
3.3
1.7
80.7
12.1
2.6
3.4
21.4
46.7
24.2
7.6
21.9
47.0
24.5
6.6
21.1
46.4
24.0
8.4
6.0
21.3
32.5
21.8
18.4
3.9
15.1
31.9
28.3
20.7
7.6
26.3
32.9
16.6
16.6
36.9
31.1
32.0
29.7
32.3
38.0
42.8
30.1
27.1
*p < .05.
**p < .01.
***p < .001.
as shown in Figure 1, the three skill dimensions
of self-reported skill, knowledge, and practical
skill were highly correlated with the latent
Internet skills variable (all ps < .001), suggesting that the latent skills variable was a valid
construct. The common fit indices suggest that
the model fit the data very well: the chi-square
index, which is used to test lack of fit of the
model, was not significant (c2 = 33.17, df = 22,
p >.05); the root mean square error of approximation (RMSEA) was .03, which is considered
an excellent fit; both the adjusted goodness of
fit index (AGFI) and the incremental fit index
(IFI) were .99, which indicate a very good fit.
DISCUSSION
The findings of this study support an Internet
usage divide with regard to political affairs.
They show that there are clear differences
between people who visit political Web sites
and those who do not in terms of political interest and Internet skill levels. Differences in
political Internet use in terms of gender,
income, and education were observed in some
of the analyses as well. The gender difference
was salient, in particular. These results resonate
with previous studies’ findings that citizens
who are active in digital civic engagements are
usually highly sophisticated, male, middleclass, and young professionals (Davis & Owen,
1998; Hill & Hughes, 1998; Norris, 1999).
In the present study, however, Internet skills
and political interest, relative to sociodemographic factors, turned out to be particularly
strong predictors of political Internet use. They
were significant consistently in all models.
Internet skills, in particular, had substantial
effects in all models, even after controlling for
the level of education. This suggests that, in the
democratic divide, which is one example of the
second-level digital divide, what matters more
are individuals’ skills and political attitudes,
Min
FIGURE 1. Structural equation model of political Internet use.
31
32
JOURNAL OF INFORMATION TECHNOLOGY & POLITICS
TABLE 2. Logistic Regression Results
Predicting Online Political Information-Seeking
and Online Political Discussion
Online political
information–seeking
Slopeb SEb
Age
Education
Gender
Income
Race
Internet skill
Political
interest
−.01
.03
.40*
.05*
.07
.23***
.93***
.01
.04
.19
.02
.27
.05
.13
Online political
discussion
EXPb Slopeb SEb
.99
1.03
1.50
1.05
1.07
1.26
2.53
.00
.02
.31
−.01
.19
.15***
.70***
.01
.04
.18
.02
.25
.04
.12
EXPb
1.00
1.03
1.37
.99
1.21
1.17
2.01
N = 606.
*p < .05.
**p < .01.
***p < .001.
Model chi-square for online political info seeking = 128.35
(df = 7). Nagelkerke’s R2 = .26.
Model chi-square for online political discussion = 71.95
(df = 7). Nagelkerke’s R2 = .15.
rather than socioeconomic or demographic factors. This resonates with recent second-level
digital divide studies that emphasize such factors as Internet efficacy and psychological attitudes (Adams et al., 2005; Eastin & LaRose,
2000). Indeed, for meaningful use of the Internet for politics, Internet skills and political
motivations would be vital.
The findings of this study, however, should
be interpreted with caution, as there are some
limitations. First, due to the inherent weakness
of the cross-sectional dataset, the findings could
not establish causality. For example, it is
unclear whether different Internet skills and
political interest caused differential use of the
Internet for politics, or whether differential use
of the Internet affected skills and interest.
Nonetheless, the study shows that Internet use
for politics is associated with social and individual divisions, which is still a meaningful
finding to understand the current political landscape on the Internet. Second, the present study
is also limited in that it did not address some
other dimensions of the democratic divide. In
the study, the democratic divide was operationalized solely as differential Internet use for politics. However, the democratic divide has multiple
dimensions, and perhaps studying the “consequences” of Internet use for politics is as important as differential use itself. How does
differential Internet use for politics translate
into meaningful differences in real-world politics? This remains an important question to be
investigated. Third, the data used in this study
were collected in 2004, and there may be
important differences between the Internet
landscape of today and then. Although the
dataset is considered high-quality, it only
addressed two dimensions of digital politics:
online political information-seeking and
online political discussion. Over the last few
years, however, new political opportunities
using the Internet such as blogging and online
citizen journalism became popular. Yet we
know very little about who is actively using
these “Web 2.0” initiatives. Are these new
political initiatives dominated by politically
sophisticated people as well? Does participating in the new initiatives require high technological skills? Further analysis is needed in
this matter.
CONCLUSION
This study attempted to portray individuals’
use of the Internet for politics. In so doing, it
found that Internet use for politics is not equal
depending on skills and motivational factors.
This may serve as a warning against the technological deterministic view that technologies
will bring a democratic utopia. Instead, what
this study suggests is that the simple availability of the new technology is not enough to
encourage the meaningful use of technology for
politics. Human interest and capacity are
equally important.
Overcoming the digital divide is not an easy
task, because in attempting to overcome one
divide, we observe the emergence of a new
usage divide. If only a certain segment of the
population uses the Internet for politics, as suggested in this study, the democratic potential of
the Internet will be undermined. Therefore, the
issue of the democratic divide warrants much
attention. One solution to this problem is to
build citizens’ digital literacy or capacity.
Min
Along with universal access to the Internet,
ongoing civic education on ICTs and their beneficial use is essential in the current information-based society. Implementing such a
program will require the full cooperation and
commitments of all parties involved—the civil
society, government, and business.
NOTES
1. The General Social Survey dataset used in this
study and relevant documentations are publicly available
from the National Opinion Research Center (NORC, http://
www.norc.org) or the Inter-University Consortium for
Political and Social Research (ICPSR, http://www.icpsr.
umich.edu).
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APPENDIX
Major Questions Used from the 2004 General Social Survey (Variable names are in
brackets)
[POL30]
772–G. In the past 30 days, how often have you visited a web site for
G) Political information
Never 1–2 times 3–5times More than 5 times
[WEBABLE]
812. Would rate your ability to use the World Wide Web as excellent, good, fair, poor or very
poor?
Excellent Good Fair Poor Very Poor
[DOWNLOAD]
791-C. Do you know how to download a file from the World Wide Web to your computer?
Yes No
[UPLOAD]
791-D. Do you know how to send a file that is on your computer’s hard drive to someone using
another computer?
Yes No
Min
35
[ADVSRCH/PREFSETS/NEWSGRPS]
815-E, H, I. Are you very familiar, somewhat familiar, or not familiar with the following Internet Terms:
E) Advanced Search
H) Preference settings
I) Newsgroups
Very familiar Somewhat familiar Not Familiar
[INTERPOL]
1468-H. Here are some different forms of political and social action that people can take. Please
indicate, for each one, whether you have done any of these things in the past year, whether
you have done it in the more distant past, whether you have not done it but might do it, or
have not done it and would never, under any circumstances, do it.
“Joined an Internet political forum or discussion group.”
[POLINT1]
1474. How interested would you say you personally are in politics?
Very interested Fairly interested Not very intereste Not at all Interested
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