National Identity and the Internet

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NATIONAL IDENTITY AND THE INTERNET
National Identity and the Internet: A Cohort Study in Hong Kong
Heng Lu 1, Tai-Quan Peng 2, Jonathan J. H. Zhu 1*
(1. Department of Media and Communication, City University of Hong Kong;
2. Faculty of Humanities and Arts, Macau University of Science and Technology)
Heng Lu (luheng9@gmail.com) is a Ph.D. candidate in the Department of Media and
Communication at the City University of Hong Kong.
Tai-Quan Peng (winsonpeng@gmail.com) is an assistant professor in the Faculty of
Humanities and Arts, Macau University of Science and Technology.
Jonathan J. H. Zhu (j.zhu@cityu.edu.hk) is a professor in the Department of Media and
Communication, City University of Hong Kong.
Proposal submitted to the 64th Annual WAPOR Conference
September 21-23, 2011
Amsterdam, The Netherlands
NATIONAL IDENTITY AND THE INTERNET
Abstract
Taking a cohort perspective, the current study investigates the effect of the Internet on
national identity in the context of Hong Kong. The national identity in contemporary Hong
Kong is theorized to be single versus hybridized identity. Employing data from a longitudinal
survey project (from 2000 to 2008) we find that the members of oldest generation are less
likely to hold a hybridized identity than the members of younger generations. Internet users
are more likely to have a hybridized identity than Internet nonusers. However, Internet users’
online behaviors are not significantly related to their national identity. Furthermore, our study
finds that the impact of Internet adoption on national identity is moderated by cohorts.
Keywords: cohort, national identity, Internet
NATIONAL IDENTITY AND THE INTERNET
National Identity and the Internet: A Cohort Study in Hong Kong
Introduction
National identity is a kind of collective identity that could be defined as an individual’s
cognitive, moral, and emotional connection with a broader community (i.e. nation) (Polletta
& Jasper, 2001). From a constructivist view, national identity is socially and historically
constructed. The development of national identity is an on-going process, which helps people
to get to know “who we are” by sharing cognitions of common origin or cultural and ethnical
characteristics with other members in the group.
Given the dynamic nature of national identity and its critical role in contemporary
political science, how national identity is constructed has become a discernible topic in
political communication research (Blumler & Kavanagh, 1999). Traditional mass media, such
as TV, newspaper, and radio, are found to play important roles in constructing and
maintaining a sense of common belonging among isolated and anonymous populations
(Anderson, 1991; Gellner, 2006; Giddens, 1991). With the increasing penetration rate of the
Internet around the world, the relationship between the Internet and national identify has
become theoretically and practically significant. Although the effect of Internet on
transnational political identification has been observed (Nisbet & Myers, 2010), the technical
potential of the Internet and other forms of computer-mediated communication (CMC) does
not automatically generate new identities (Waisbord, 1998). The social identity model of
deindividuation effects (SIDE) model suggests that CMC would reinforce the social
boundaries because of that in the context of anonymous CMC communicators appear to be
more susceptible to group influence (Postmes, Spears, & Lea, 1998).
Our study adopts a cohort perspective to examine the relationship between the Internet
and national identity. It has been emphasized that “social location” of identity construction is
NATIONAL IDENTITY AND THE INTERNET
cohort-dependent (Griffin, 2004). National identity construction and reconstruction depends
heavily on generational experiences, as cohorts construct different collective identities based
on what they experience at the time they enter their social lives.
National identity in Hong Kong has been raised as a political and cultural issue since the
1970s. Because of the historical and social transition of pre- and post-colonial Hong Kong,
national identity in Hong Kong has no obvious nationalistic component. In other words, local
identity (i.e., Hong Kong identity) and national identity (i.e., China identity) is not mutually
exclusive in Hong Kong (Fung, 2004; Lee & Chan, 2005; Ma & Fung, 2007). Meanwhile, the
Internet has penetrated into multi-aspects of individuals’ lives in Hong Kong, with Internet
penetration rate increasing steadily from 40% in 2000 to 69% in 20081. Therefore, Hong
Kong provides an ideal platform to examine the intricate interactions between the Internet
and national identity from a longitudinal perspective.
The current work has the following objectives: (1) To describe the cohort trend of
national identity in Hong Kong; (2) To empirically examine the effects of Internet adoption
and Internet use on national identity respectively; (3) To uncover the conditional effect of the
generational cohort on the relationship between Internet adoption/use and national identity.
National Identity in the Hong Kong Context
As a specific form of social identity, national identity is “discursively, by means of
language and other semiotic systems, produced, reproduced, transformed and destructed” (De
Cillia, Reisigl, & Wodak, 1999, p. 153). It is the basis on which people could define and
locate themselves in the world. Hong Kong identity is an arguable issue. “Hong Kong
people” (i.e., Hong Kongers) identify themselves with their distinctive history, lifestyle and
1
The Internet penetration rate of Hong Kong can be obtained at http://newmedia.cityu.edu.hk/hkip/.
NATIONAL IDENTITY AND THE INTERNET
culture. For Hong Kongers, there is no nationalistic imperative that they should belong to a
certain nation (e.g., the Great Britain or PRC). Hong Kong identity does not have a political
affiliation with any sovereign state: certainly not Great Britain, and for most, nor China either
(Ma & Fung, 2007). Nevertheless, the Hong Kong identity is historically and culturally real.
The local (i.e., Hong Kong) and national (i.e., China) identity dichotomy was the main
theoretical framework of research on Hong Kong identity since late 1970s and before 1997.
As the end of the colonial government was approaching, the idea of “one country, two
systems” was proposed by Deng Xiaoping, then paramount leader of the PRC, for the
reunification of China in the early 1980s. To some extent, the rise of local identity is
responding and contesting to the “one country” principle. When the return of Hong Kong to
China seems to be clear in the mid-1980s, Hong Kong people tend to raise strong defense for
their identity. This dual nature of local/nation identity indicates that the greater cognitive
distance between Hong Konger’s self-image and their image of mainland Chinese, the
stronger they attach themselves to the localized identity of Hong Kong (Lau, 1997, 2000).
The convergence of political structures since 1997 curbs the development of Hong Kong
local identity. It has been found that the return of Hong Kong to China narrows the cultural
distance between Hong Kongers and mainland Chinese and blurs the boundary between the
Hong Kong local identity and China nation identity (Fung, 2004; Lee & Chan, 2005; Ma &
Fung, 2007). Lee and Chan (2005) suggest the dichotomy of a “Hongkongese” vs. a
“Chinese” identity can no longer capture the central issue of identity in today’s Hong Kong.
They propose multiple constructs of Hong Kong identities (i.e., Hongkongese, Chinese, Hong
Kong’s Chinese, and China’s Hongkongese) and support the categorization with HK opinion
polls results after 1997. Ma and Fung (2007) find that Hong Kongers are claiming a mixed
local and national identity. The changing of identity involves the perception of the local
NATIONAL IDENTITY AND THE INTERNET
identity within, the reaction to the external nationalization, and the adaptation to the political
context. HK identity becomes increasingly hybridized between the local and national identity.
The hybridized categorization of Hong Kong identity is empirically validated and well
documented in academic research. Researchers usually combine the categories of
“Hongkongese” and “Hong Kong’s Chinese” together to represent a local identity and that of
“Chinese” and “China’s Hongkongese” together to represent a national identity (Fung, 2004).
However, such combination overlooks another important theoretical issue: why some people
would like to hold a hybridized/mixed identity while some other people would like to hold a
sharply defined local or national identity. Ma and Fung (2007) observed that the national and
local identifications have started to merge. The issue of single (e.g., Hongkongnese, Chinese)
versus hybridized (e.g., Hong Kong’s Chinese, China’s Hongkongese) identity becomes an
interesting and important theoretical issue which needs more investigations. In the current
study, we adopt the above classification of single and hybridized national identity here and
after.
National Identity, Cohort, and the Internet
Although empirical studies on “national identity” or “identity politics” have grown in
recent years (e.g., McCrone, Stewart, Kiely, & Bechhofer, 1998; Rawnsley & Rawnsley,
2003), there is few literature addressing the effect of the Internet on national identity from a
cohort perspective. In fact, there are reasons to believe that the Internet would have particular
effects on national identity and a cohort perspective is needed in order to better understand
such effects. To fill in the gap in the literature, our study adopts a cohort perspective to
examine the effect of the Internet on national identity in Hong Kong. Specifically, we
investigate the effects of (1) Cohort, (2) Internet adoption, (3) Internet use, and (4) the
interaction effects between the Internet and cohort on national identity in the Hong Kong
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context.
Firstly, national identity is cohort-dependent (Blank & Schmidt, 2003; Griffin, 2004; Lutz,
Kritzinger, & Skirbekk, 2006). The notion of generation/cohort is raised as a sociological
theoretical issue by Mannheim a long time ago:
The fact of belonging to the same class, and that of belonging to the same generation or
age group, have this in common, that both endow the individuals sharing in them with a
common location in the social and historical process, and thereby limit them to a
specific range of potential experience, predisposing them for a certain characteristic
mode of thought and experience, and a characteristic type of historically relevant action
(Mannheim, 1952, p. 291).
Cohort effect stands for the social impact on individuals’ attitudes and/or behaviors.
Individuals who belong to the same generation are socialized in a similar way because of
their exposure to the same significant historical events. Generational differences in respect of
political attitude and behavior could be the result of (1) differential exposure to significant
historical events, and (2) changes in the processes and content of socialization (Klecka, 1971).
According to Inglehart (1977, 1990), the exposure to historical events of national significance
(especially for those who reach political maturity by the time) will influence the values,
attitudes, beliefs, and behaviors of individuals. In particular, such kind of generational
differences tends to be greater in countries that have higher rates of economic growth
(Abramson & Inglehart, 1995). In fact, cohort effects have been empirically found among
various political attitudes, such as supportive of educational spending (Fullerton & Dixon,
2010; Plutzer & Berkman, 2005), party identification (Cassel, 1977), and national pride (T. W.
Smith & Kim, 2006). In the context of Hong Kong, different cohorts experience different
stages of political transitions. Therefore, we argue that the national identifications are
different among members of different cohorts. Specifically, we hypothesize that:
H1. The younger cohort an individual belongs to, the more likely he/she will have a
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hybridized national identity.
Secondly, the Internet is changing the way we create and experience our identities. CMC
via the Internet will also cause an influence on national identity by affecting our perceptions
of social boundaries. The complex nature of online interactions over the Internet is
influencing their identification, because national identification is always a process of dealing
with distinguishing “us” from “the others”. The Internet provides a symbolic environment
which is not necessarily bounded by the real world boundaries (Meyrowitz, 1985). The issue
of Internet and other forms of CMC would build or destroy the social boundaries is
theoretically debatable (Postmes, et al., 1998; Waisbord, 1998). Hiltz and Turoff (1978)
suggest that the CMC breaks down the social boundaries and then create a “network nation”.
However, they soon realize that they are over-optimism about that. “The social systems do
not change rapidly or easily” (Hiltz & Turoff, 1993, p. xxix). We argue that even if the social
boundaries are not easily to break down, CMC will provide the resources that can be used by
individuals to redraw the social boundaries for groups and individuals, especially in the
context of Internet.
Empirical studies have found that uses of traditional media will affect individuals’
national identity. For example, the readers of French-language newspapers have significantly
more positive feelings toward the province of Quebec and more negative assessments of the
nation of Canada (Antecol & Endersby, 1999); the exposure to transnational TV increases the
probability of transnational political identification rather than that of national identification
(Nisbet & Myers, 2010). In the case of the Internet, although limited in quantity, empirical
evidences are found to support the effect of Internet use on national identity construction.
Smith and Phillips (2006) find that exposure to the Internet will weaken individuals’ national
attachment. Therefore, we hypothesize that Internet adoption will increase one’s attachment
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to a hybridized identity. Specifically,
H2. Internet users are more likely to have a hybridized national identity than Internet
non-users.
We further decomposing Internet use into two dimensions: online time and diversity of
webpage browsing. Specifically, we set up the following hypotheses:
H3a. The more time an individual spends on the Internet, the more likely he/she will have
a hybridized national identity.
H3b. The more diverse websites an Internet user visits, the more likely he/she will have a
hybridized national identity.
Thirdly, the effect of the Internet on national identity could be cohort dependent. The
generational differences with regard to political attitudes (e.g., national identification) may be
caused by the different experiences of socialization in different contexts, or a change in the
composition of the population (i.e., changing numbers of individuals with certain individual
attributes), or a combination of the above two (Alwin, 1990). In case of Internet use, on the
one hand, the younger and older cohorts start to use Internet at different life stages. On the
other hand, with the process of the Internet diffusion, the heterogeneity of the Internet
user-population increases, especially in terms of socioeconomic status. Therefore, the effects
of the Internet on political attitudes may not be identical across different generations. Peng
and Zhu (2008) find significant differences between Internet users and nonusers in Internet
political efficacy for mid-age cohorts, but not for the youngest and the oldest cohorts.
Jennings and Zeitner (2003) find that the effect of the Internet on civic engagement differs
between upcoming and contemporary adult generations. Therefore, we also examine the
interaction effect between cohort and the Internet on national identity. The fourth hypothesis
in respect to the interaction effect is stated as follows:
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H4. The effect of Internet adoption on Hong Kong identity is moderated by cohorts.
Methodology
The data of this study come from a series of annual telephone surveys in Hong Kong at
the end of every year from 2000 to 2008 (except for 2007). The study population of annual
surveys is those regular residents between 6 to 84 years old who speak Chinese (including
Mandarin, Cantonese, and other dialectics) and live in Hong Kong. Random digital dialing
(RDD) method is used to generate the sample of every survey.
The sample sizes for every survey are about 1,000 per year. Calculated by Response Rate
Formulae 3 (RR3) of the American Association for Public Opinion Research (AAPOR, 2006),
the response rate of nine surveys are about 30%. The data have been weighted against Hong
Kong population Census Estimates each year, in terms of cross-distribution of age and sex.
Measurement
Individuals’ national identities in Hong Kong are classified into four categories along
with two dimensions as shown in Appendix
Figure 1. The first dimension is national-local dimension and the second is single-hybrid
dimension. Four categories of national identities are provided for respondents to answer the
following question – ‘Since 1997 when Hong Kong returned to China, what is the national
identity of Hong Kong residents you think”. Respondents could choose only one answer from
a list of four: 1. Chinese; 2. Hong Konger; 3. Chinese first, then Hong Konger; 4. Hong
Konger first, then Chinese. National identity is treated as a dichotomy variable in this study.
One attribute of national identity is “single identity” which is a combination of “Chinese” and
“Hong Konger”; another attribute of national identity is “hybridized identity” which is a
combination of “Chinese first, then Hong Konger” and “Hong Konger first, then Chinese”.
Figure 1 about here
NATIONAL IDENTITY AND THE INTERNET
Respondents are asked to indicate their Internet adoption status as three categories: user,
non-user, and discontinued user (i.e. individuals used the Internet before but not now). In this
study, the variable is recoded into two categories with 1 equal to user and 0 equal to non-user
by combining the last two categories.
Internet usage is measured in two dimensions: online time and diversity of web browsing.
Online time is measured by asking respondents to report how many hours they spend on the
Internet per week.
Webpage browsing is one of the main activities individuals engage on the Internet.
Respondents are asked to report what percentages of their total webpage browsing time are
spent on the following four kinds of websites: (1) overseas Chinese websites; (2) overseas
non-Chinese websites; (3) domestic Chinese websites; (4) domestic non-Chinese websites.
Based on these four measures, a H-score representing the Diversity of Webpage-browsing
is calculated with the equation for entropy in information theory (Shannon & Weaver, 1949),
which has been used to calculate the diversity of online time (Zhu & He, 2002) and the
diversity of online place (Peng & Zhu, 2011):
k
H   Pi (log 2 Pi )
i 1
where H is the summary score of diversity, Pi is the proportion of the total online time
spent at the ith kind of website (i=1 to 4 in the current study), log2 is the logarithm with 2 as
the base, and the minus sign is to offset the negative values resulting from the logarithm
transformation of percentages (i.e., less than 100%). The H-statistics is not affected by the
amount of webpage-browsing time but related to the distribution of time on different websites.
The more evenly a user spreads his/her online time across different websites, the higher
his/her H score is. If a user uniformly allocates one-fourth of his online time to each of the
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three places, he/she will receive a maximum diversity score (2), whereas if a user allocates all
the time at a single kind of website, he/she will receive a minimum diversity score (0),
regardless of how much time per week the users spend on browsing webpages.
Four generational cohorts are constructed in the sample according to Lui’s (2007)
description and analysis. The characteristics and lifestyles of the four generations of Hong
Kong people are quite different. The members of the first cohort are born before 1945, many
of whom escaped from the PRC and took refuge in Hong Kong during the Sino-Japanese war.
The first cohort is termed as Seniors. Those born between 1946 and 1965 are members of the
second cohort, termed as Baby Boom Generation. Many of them are the post-war baby
boomers. The third cohort, termed as Generation X, includes those born between 1966 and
1975, many of whom are young children of the Seniors or younger siblings of baby boomers.
The members of the fourth cohort are born between 1976 and 1990, many of whom are
offspring of baby boomers. This cohort is termed as Generation Y.
Four demographic variables are included in the current study: gender, family income, and
education level. Gender is measured as a dichotomous variable with 0 equal to male and 1
equal to female. Family income is measured by asking respondents to report their family
income which ranges from 1 representing ‘less than HK$5,000’ to 13 representing ‘more than
HK$100,001’. Education level is measured by asking respondents to report their highest
obtained education degree which ranges from 1 representing ‘elementary school or less’ to 6
representing ‘postgraduates’.
Analysis Design
Because the dependent variable, National Identity, is constructed as a dichotomy variable
(i.e., single versus hybridized identity), logistic regressions are employed in the study to
investigate the impact of demographic variables, cohort, Internet adoption, and Internet usage
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on the preference for the two types of national identities. To test our research hypotheses on
the predictors of national identity, we estimate five logistic regressions and present the logits
(B), the standard errors (S.E.) and the odds (eB). We start with a model containing only the
year of survey (period) and cohort (Model 1), then included demographic variables (Model 2).
In the third and fourth model, we add Internet adoption and Internet use (i.e., online time and
diversity of webpage browsing) to Model 2, respectively. Finally, we add interaction terms
between the Internet adoption and cohort to the fifth model based on Model 3 to test the
interaction effects. The Model 1, 2, 3, and 5 are for the overall sample including both users
and nonusers of the Internet, whereas the Model 4 is exclusively for users.
Results
Table 1 presents the number of individuals who are nested within cells of generational
cohorts and survey years. Each row is a cohort and each column is a survey year. The number
of valid cases of each year of the survey is ranging from 879 (Year 2006) to 1,357 (Year 2002)
with an average of 1,031. The Baby Boom Generation is the largest cohort (47% of the
population on average) while the Generation Y is the smallest (14% of the population on
average). The oldest cohort member was born in 1925 and the youngest born in 1982.
Table 1 about here
Variable descriptions and summary univariate statistics for the data used in logistic
regressions are shown in Table 2.
Table 2 about here
As shown in Table 3, Model 1 examines the effects of study periods and cohorts on
national identity. As shown in Figure 2,the number of individuals
holding a hybridized
identity in Hong Kong changes over study periods, ranging from 37 percent of the population
(Year 2002) to 50 percent (Year 2005).
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Figure 2 about here
Moreover, cohorts differ significantly in their national identity. Individuals of Baby
Boom Generation, Generation X, and Generation Y are more likely to hold a hybridized
identity than that of Seniors as shown in Figure 2.
When other demographic variables are included into the model, it is found that
individuals with higher degree of education or higher income are more likely to hold a
hybridized identity. In the second model, the effects of cohorts still exist. That’s to say, the
cohort effects are not merely caused by the change in the composition of population itself.
Generational differences in national identifications could, at least partly, explain the observed
trends in Hong Kong identity. We also test the Model 2 with Baby Boom Generation,
Generation X, and Generation Y as reference group, respectively. We find that the significant
difference in national identification only exists between Seniors and other generations. There
are no significant differences among Baby Boom Generation, Generation X, and Generation
Y. Therefore, H1 is partially supported.
Table 3 about here
Internet users are found to be more likely to hold a hybridized identity than nonusers with
period, cohort, and demographic variables controlled. Model 3 of Table 3, incorporates
Internet adoption as an antecedent of national identity, which aims to compare Internet users’
national identity with nonusers’ identity. We find that the odds for Internet users holding a
hybridized identity are about 37% higher than that for nonusers. The model explains 10% of
the total variances. Figure 3 demonstrates the effect of Internet adoption on national identity.
Therefore, H2 is fully supported.
Figure 3 about here
Now the spotlight turns to Internet users. We examine the effect of Internet use on
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national identity by incorporating online time and diversity of webpage browsing as
antecedents of national identity. However, neither online time nor diversity of webpage
browsing exerts significant influences on Internet users’ national identity.
Therefore, H3a
and H3b are not supported.
In Model 5, in Table 3, we include the interaction terms between cohort and Internet
adoption to test the interaction effects. We test the model with the interaction term between
Internet adoption and Seniors, Baby Boom Generation, and Generation X as reference group,
respectively.
It is found that the impact of Internet adoption on national identity is conditioned by some,
if not all, generational cohorts. Specifically, for Generation X, the odds for Internet users
claiming a hybridized identity are about 100% higher than the odds for nonusers. For Baby
Boom Generation and Generation Y, the odds for Internet users claiming a hybridized
identity are about 37% (100% - 63%) and 45% (100% - 55%) higher than the odds for
nonusers, respectively. Figure 3 also demonstrates the above interaction effects between the
Internet adoption and cohorts. The gap between Internet users and nonusers for Generation X
is wider than that for Baby Boom Generation and Generation Y. Therefore, H4 is supported.
We also examine the interaction effects between Internet use in terms of online time and
diversity of webpage browsing and cohorts on national identity. However, neither Internet
use nor its interaction with cohorts exerts significant influences on Internet users’ national
identity.
Although not formally hypothesized, we find that gender, level of income and education
are significant predictors of Hong Kong identity. As presented in Model 5 in Table 3, the odds
for female claiming a hybridized identity are about 13% higher than the odds for males; for a
one-unit increase in income and educational level, we expect to see about 4% and 17%
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increase in the odds of claiming a hybridized identity, respectively.
Discussion
The current study uncovers the cohort trends of national identity in Hong Kong. The
members of oldest generation are less likely to hold a hybridized identity than the members
of younger generations. Internet users are more likely to have a hybridized identity than
Internet nonusers. However, Internet users’ online behaviors are not significantly related to
their national identity. Furthermore, our study finds that the impact of Internet adoption on
national identity is moderated by cohorts. The effect of the Internet adoption on national
identity is greatest for the members of Generation X (20 percent of the population), who was
born between 1966 and 1975. We also confirm that the cohort effects operate even after
controlling for the changing composition of society with regard to gender, income and
educational level. That’s to say, the generational differences in respect to the exposure to
significant historical events have certain impacts on individuals’ national identifications.
Our study also contributes to the theorization of national identity in the context of
contemporary societies. The hybridized local-national identity is a reflection of the support of
the two identity authorities by Hong Kong people (Fung, 2004). While the previous studies
usually adopt a perspective of local versus national identity, we employ a perspective of
single versus hybridized identity. The hybridized national identity does not mean that local
has subsumed into the national or vice versa. It means a positive and open-minded attitude
toward “others”. The issue of identity is increasingly important as the development of
globalization (Morley & Robins, 1995) and transnational politics (Herrmann, Risse-Kappen,
& Brewer, 2004). Our perspective could be generalized to other contexts. The globalization
and formation of transnational identity may not accompany with the identity crisis. We can
learn from the Hong Kong experiences that the individuals could support dual authorities.
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The important theoretical issue in respect to identity underling the development of
globalization and transnational politics is to what extent the individuals take open-minded
attitudes toward “others” — the alternative authority. As such, the identity does not have to
be analyzed in regards to local versus national or national versus supranational. The
perspective of single versus hybridized identity would better capture the core issue of identity
in contemporary societies.
Although with the increasing penetration rate of the Internet, eventually, most of people
would be Internet users; our study traces the longitudinal trends of the effects of Internet on
national identity with the penetration rate of the Internet increases from 41% in 2002 to 69%
in 2008 in Hong Kong. Such kind of longitudinal perspective provides us great opportunities
to observe the cohort effects. The impact of one’s generation on national identity also has
been found elsewhere, e.g., Japan (Sasaki, 2004) and EU (Lutz, et al., 2006). Our findings
confirmed that the cohort effects exist even after controlling for the change in composition of
population itself.
The effect of Internet use on national identity has not been confirmed in our study. That’s
partly because our measurement of Internet use is over simplified. The previous study finds
that the genre of media content is more powerful predictor of national identity than media
channel (P. Smith & Phillips, 2006). Future studies on the relationship between Internet use
and national identity should further decompose the Internet use and zoom into the genres of
online content.
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Appendix
Figure 1. Categorization of National Identities in Hong Kong
21
NATIONAL IDENTITY AND THE INTERNET
Figure 2. The Number of Hong Kongers (in percentage) Holding a Hybridized National Identity by Cohorts by Period
22
NATIONAL IDENTITY AND THE INTERNET
Figure 3. The Number of Hong Kongers (in percentage) Holding a Hybridized National Identity by Internet Adoption by Cohorts
23
NATIONAL IDENTITY AND THE INTERNET
Table 1. Number of Observations in Each Cohort-by-Period Cell (percentage in parentheses)
Cohort
Seniors
Baby Boom Generation
Generation X
Generation Y
Total
2000
197
(20)
473
(47)
206
(21)
131
(13)
1,007
(100)
2001
175
(20)
423
(48)
167
(19)
126
(14)
891
(100)
2002
283
(21)
632
(47)
269
(20)
173
(13)
1,357
(100)
2003
231
(21)
522
(47)
178
(16)
170
(15)
1,101
(100)
Year
2004
202
(19)
493
(47)
208
(20)
151
(14)
1,054
(100)
2005
161
(18)
423
(47)
199
(22)
113
(13)
896
(100)
2006
157
(18)
416
(47)
172
(20)
134
(15)
879
(100)
2008
179
(17)
480
(45)
227
(21)
176
(17)
1,062
(100)
Total
1,708
(19)
4,206
(47)
1,791
(20)
1,260
(14)
8,247
(100)
24
NATIONAL IDENTITY AND THE INTERNET
Table 2. Summary Statistics for Variables Used in Regression Models
Identity
Internet Adoption
Online Time
Diversity of Webpage
Browsing
Gender
Educational Level
Income Level
Period
Cohort
Description
Single identity = 0; Hybirdized identity = 1
Nonuser = 0; User = 1
Number of hours spent online per week
H-score of diversity
Male = 0; Female = 1
Ranging from 1 representing ‘elementary school or
less’ to 6 representing ‘postgraduates’
Ranging from 1 representing ‘less than HK$5,000’ to
13 representing ‘more than HK$100,001’
Survey year
Lui's (2007) typology of Hong Kong's four generations
N
7,924
8,243
3,717
Std.
Mean Deviation
0.43
0.50
0.49
0.50
15.25
18.92
Min
0
0
0
Max
1
1
192
2,693
8,245
0.82
0.52
0.35
0.50
0
0
1.39
1
8,046
3.10
1.76
1
7
6,464
8
4
4.79
2.89
1
2000
1925
12
2008
1982
25
NATIONAL IDENTITY AND THE INTERNET
Table 3. Logistic Regression Models for National Identity (Reference = Single Identity)
Model 1
B
Model 2
S.E.
eB
B
Model 3
S.E.
eB
Model 4
B
S.E.
eB
B
Model 5
S.E.
eB
B
S.E.
eB
Period (Reference = 2000)
2001
0.143
0.098
1.154
0.226
0.118
1.254
0.217
0.118
1.242
-0.094
0.218
0.910
0.216
0.118
1.242
2002
-0.136
0.089
0.872
-0.044
0.107
0.957
-0.057
0.107
0.945
-0.354*
0.151
0.702
-0.058
0.107
0.944
2003
0.073
0.092
1.076
0.111
0.107
1.118
0.090
0.107
1.094
-0.092
0.152
0.912
0.092
0.107
1.097
2004
-0.031
0.093
0.969
-0.045
0.108
0.956
-0.078
0.108
0.925
-0.286
0.148
0.751
-0.079
0.109
0.924
2005
0.366***
0.097
1.443
0.358**
0.112
1.430
0.315**
0.113
1.370
0.079
0.161
1.082
0.312**
0.113
1.366
2006
0.325**
0.097
1.385
0.291**
0.111
1.338
0.244**
0.112
1.276
0.108
0.153
1.114
0.240*
0.112
1.271
2008
0.174
0.092
1.190
0.267*
0.107
1.306
0.209
0.108
1.232
0.203
0.108
1.225
-0.248
0.141
0.781
0.324*
0.126
1.383
Cohort (For Model 1-4, Reference = Seniors; For Model 5, Reference = Generation X)
Seniors
Baby Boom Generation
0.806***
0.069
2.239
0.613***
0.086
1.847
0.531***
0.088
1.701
0.336
0.305
1.400
Generation X
1.093***
0.079
2.983
0.667***
0.098
1.948
0.533***
0.102
1.704
0.448
0.309
1.566
Generation Y
1.154***
0.084
3.170
0.716***
0.106
2.046
0.565***
0.111
1.759
0.367
0.311
1.444
0.502*
0.203
1.653
Gender (Reference = Male)
0.101
0.053
1.106
0.119*
0.054
1.126
0.207*
0.092
1.230
0.122*
0.054
1.130
Educational Level
0.189***
0.019
1.208
0.159***
0.020
1.172
0.116***
0.033
1.124
0.161***
0.020
1.174
Income
0.047***
0.011
1.048
0.037**
0.011
1.038
0.010
0.018
1.010
0.036**
0.011
1.037
0.313***
0.067
1.367
0.694***
0.135
2.002
-0.394
0.267
0.675
Control Variables and Intercept
Internet
Internet adoption
Online Time (log-transformed)
0.068
0.096
1.071
Diversity of Web Browsing
-0.258
0.136
0.773
Interaction (Reference = Generation X × Adoption)
Senior × Adoption
26
NATIONAL IDENTITY AND THE INTERNET
BabyBoomGeneration × Adoption
-0.468**
0.151
0.626
GenerationY × Adoption
-0.603**
0.225
0.547
-1.573***
0.176
0.207
Intercept
-1.153***
-2 Log Likelihood
10521.9
8213.4
8190.3
2856.4
8178.9

318.3
442.6
463.2
48.1
474.6
10
13
14
14
17
0.053
0.091
0.095
0.030
0.097
7357
5844
5843
1942
5843
2
df
Nagelkerke R
N
2
0.087
0.316
-1.887***
0.143
0.152
-1.817***
0.144
0.163
-0.681
0.371
0.506
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