Journal of Computer-Mediated Communication
Mapping Diversities and Tracing Trends of
Cultural Homogeneity/Heterogeneity
in Cyberspace
Elad Segev
School of Politics, International Relations, & Philosophy
Keele University
Niv Ahituv
The Faculty of Management
Tel Aviv University
Karine Barzilai-Nahon
The Information School
University of Washington
Many Internet global commercial services were originally initiated in the United States
and later exported to other countries, continents, and cultures. By analyzing content
and form characteristics of two leading portal sites—MSN and Yahoo!—on 33 and 23
(respectively) of their local country homepages in a comparative and longitudinal study
over a period of six months, this study addresses two research questions: What differences, if any, are found among homepages of the same parent site located in different
cultures (or targeted at audiences in different cultures)? What trends, if any, do those
differences show over time? Although MSN is a U.S. brand, the analysis of its homepages reveals increasing cultural heterogeneity and localization of content and form. In
contrast, Yahoo!’s homepages are found to be more similar to each other and to the
‘‘parent’’ American portal. A metric was developed to measure the distance between various websites in terms of form and content, along with a structured procedure to analyze
and cluster groups of websites. The results suggest that the diversity of local homepages
in MSN and Yahoo! follows the geographic and ethnographic scatter of their countries.
doi:10.1111/j.1083-6101.2007.00373.x
Introduction
Many Internet global commercial services (news portals, ISPs, weather portals, and
the like) were originally initiated in the United States and later exported to other
countries, continents, and cultures. An interesting question is to what extent cultural
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1269
variance is reflected through the Internet and whether one dominant culture, such as
that of the U.S., enforces cultural homogeneity in cyberspace. The Internet is a unique
cultural space in that it combines a variety of means and forms of communication
(e.g., mutual interaction, broadcasting, self-searching for information, forum
groups, human computer interaction) and different types of content (e.g., text,
image, voice, video). This provides a wide range of opportunities, which in turn
have significant social and cultural implications (DiMaggio, Hargittai, Neuman, &
Robinson, 2001).
Cultural Diversity in Cyberspace
Some scholars have suggested that mass communication channels shaped by early
media forms (e.g., written press, radio, television) might create a global uniform
taste. They argued that commercial considerations and dependence on advertisements might produce homogeneous and popular programs or texts in order to
attract the attention of maximally large audiences (Adorno, 1991; Bagdikian, 2004;
Mattelart, 1991; Shils, 1963). Eventually, together with the advent of the Internet and
the increasing availability and openness of information (Ahituv, 2001), some media
channels would be likely to represent a certain universal homogeneity. This claim
stands in contrast to the increasing customization of production (Caves, 2000;
Shapiro & Varian, 1999; Sunstein, 2001) and the long-tail theory, which shows that
profit follows the economics of abundance (Anderson, 2006).
Other researchers suggest that economic imperatives will keep the Internet from
realizing its technical potential as a source of cultural abundance (Castells, 1996;
Neuman, McKnight, & Solomon, 1998). They indicate that although entrance barriers to the network may be low, competitors can bias the attention of users and
consequently confine it (Barzilai-Nahon, 2006). In fact, 80% of visits are to only
0.5% of websites (Waxman, 2000). Similarly, some scholars suggest that online
information is not equally spread throughout the global network but rather is channeled by economic, technological, cultural, and social factors (Barabási, 2001). From
this perspective, online information is controlled by dominant actors and is concentrated in ‘‘live-zones,’’ i.e., information-saturated centers that have a global cultural
impact (Kellerman, 2002; Lash, 2002). Moreover, evidence has been reported that the
English language dominates online content out of proportion to its share of native
speaker Internet users (Global Reach, 2004).
The question is whether the Internet promotes individual and local expressions
and therefore heterogeneous culture, or whether it serves as an instrument for
dominant organizations (and nations) to increase markets and reinforce common,
homogeneous dispositions. This study proposes quantitative tools to explore cultural heterogeneity through popular online artifacts. The idea of exploiting quantitative tools to study cultural differences is not new in the social sciences; however, the
attempt to establish a metrics of distance between the content and form of different
websites is quite new.
1270Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
A recent study by Norris (2004) measured the bridging and bonding functions of
various online groups in the context of ideological, political, and social homogeneity
and heterogeneity. Her study used an ordinary least squares (OLS) regression model
to predict these measures, while taking into account cultural attributes such as
interests, lifestyle, religious group, and more.
Hofstede (1997) suggested that national culture has significant implications for
organizational behavior. He defined culture as ‘‘the collective mental programming’’
(p. 5) that occurs along various dimensions. Hofstede measured cultural differences
in the workplace using survey data from IBM employees in over 50 countries.
Ultimately, he designed a special index for each dimension and ranked the countries
by their cultural differences in the workplace.
Content and Form as Cultural Artifacts
Various recent studies have implemented Hofstede’s (1997) framework to explore
the design and content of websites in different countries (Callahan, 2005; Cyr &
Trevor-Smith, 2004; Lo & Gong, 2005; Sheridan, 2001; Zhao, Massey, Murphy, &
Liu, 2003). Their findings suggest that differences in website form and content reflect
a variety of cultural attributes. Relatedly, a recent study by Würtz (2005) compared
the form and content of transnational corporation websites in different countries. It
revealed that the websites of high-context cultures (Hall & Hall, 1990) such as Japan,
China, and Korea, in which communication is relatively indirect and rich in gestures,
displayed more extensive use of graphic elements and indirect messages. By contrast,
websites of low-context cultures, such as Germany, Norway, and the U.S., in which
communication is relatively direct, were more static and displayed rather direct
messages. In terms of content, it was found that websites of high-context cultures
tended to emphasize family and social values, while websites of low-context cultures
tended to emphasize freedom and personal lifestyle. Similar trends were observed in
other studies (Leonardi, 2002; Marcus & Gould, 2000), indicating that different
national websites place different emphases on collective and individual values.
While a growing number of studies have focused on website design and layout
(e.g., animations, colors, graphical density, and navigation menus) as cultural
markers (Badre, 2000; Becker, 2002; Callahan, 2005; Cyr & Trevor-Smith, 2004;
Sun, 2001; Tsui & Paynter, 2004), fewer studies have been conducted on differences
in content and their cultural implications. Most content analyses are based on
Hofstede’s (1997) frameworks and thus are limited in focus.
Robbins and Stylianou (2003) looked at the information provided by the largest
global corporation websites. They found that website content is significantly different
across national cultures. Singh and Baack (2004), Singh, Furrer, and Ostinelli (2004),
and Singh, Xhao, and Hu (2003) compared the content of American, Mexican,
European, Indian, and Chinese websites, identifying significant differences in
emphasis on family and social values, masculinity, and power. Additionally, the
authors argued that online users prefer localized over standardized web content.
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1271
In contrast to cultural sensitivity and localization of content and form, Kang and
Corbitt (2001) revealed trends of homogeneity and standardization in web design.
They examined the differences in display colors, images, animation, and functionality of 10 U.S.-based IT companies and their Australian and Singaporean versions.
Their study concluded that local homepages used a design similar to the parent U.S.
website, taking only minor account of cultural issues.
Finally, a study by Schmied (2003) looked at websites of transnational corporations, and particularly websites of airline companies, finding certain trends of
standardization in content and form, but at the same time identifying distinctive
local cultural markers. In short, there are very few studies that indicate trends of
homogeneity in web design and content, and even then their findings still suggest
that there are local elements that cannot be ignored.
By exploring cultural diversity through differences in the content and form of
national homepages, it is presumed that online culture may be reflected through
content and form. Barber and Badre (1998) defined the term ‘‘culturability’’ as the
relationship between culture and usability in the design of webpages. They argued
that the interface design, interactivity and content reflect cultural sensitivity and
understanding of the targeted audience. Their study indicated that there are design
patterns (or what they also called ‘‘cultural markers’’), which are highly prevalent
within different cultures and different genres. Their study indicates, for example, that
Brazilian websites tend to be more colorful and Lebanese websites tend to use light
graphics and more text (Badre, 2000; Barber & Badre, 1998). Similarly, the present
study uses the term ‘‘culture’’ somewhat loosely, as a means to distinguish among the
different countries and their respective websites. There is no intention to explore the
various aspects of this term but rather to enable a comparison of national websites as
cultural products or ‘‘artifacts’’ (Appadurai, 1996) with different form and content
attributes. Thus, the term ‘‘online culture’’ is used here to refer to national cultures as
reflected on the Internet.
While most of the aforementioned studies compared content and form elements
using Hofstede’s framework, in this study we develop an original metric to measure
the diversity of content and form online. We choose to study the Internet portals
MSN and Yahoo! mainly due to their significant rating and popularity in the
observed countries (Nielsen/Netratings, 2004; see also Appendix C). We focus on
the differences in their local homepages, assuming that the previous decisions of web
designers and corporate strategies are incorporated in their content and form, and
that they are constantly affected by the values and norms of their local audiences.
Van Couvering (2004) suggested that MSN and Yahoo! conform to the mass
communication business model known as the ‘‘dual product’’ market. On the one
hand, they produce cultural artifacts for individuals, and on the other hand, they
produce advertisements. But here the business models of MSN and Yahoo! differ, in
that MSN gets 29% of its revenue from advertisements, while Yahoo! gets 82% of its
revenue from advertisements (Van Couvering, 2004). These different revenue strategies also suggest that MSN benefits more from direct subscription, and therefore
1272Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
compels its customers to pay more attention to local and customized cultural artifacts, than its competitor Yahoo!. Consequently, it was expected that the content and
form of national homepages in MSN would be more diverse and localized than in
Yahoo!. The results of this study strongly support that hypothesis.
Research Questions
This article addressed two primary research questions:
RQ1: What are the differences in content and form among local homepages of the same parent
site?
RQ2: What trends, if any, do these differences display over a period of time?
The first question explores diversity and raises sub-questions such as: What are
the similarities of each homepage to the parent U.S. site? Is there any relation
between geographical or ethnographical diversity and online cultural diversity?
The second question explores trends and raises sub-questions such as: Is it possible
to trace trends in content and form of popular Internet portals? If so, are they
progressing toward cultural homogeneity or toward heterogeneity?
Since both MSN and Yahoo! originated in the U.S., we expected to find cultural
homogeneity in local homepages, reflecting the form and content of the parent U.S.
site, and an increasing similarity in their form and content over time.
Methodology
In order to capture the content and form of different local homepages, an observation item list was constructed. The item list is an electronic form that was used to
report content and form in the different local homepages of MSN and Yahoo!. One
month of observations (May 2003) served as a pilot sample to fine-tune the item list.
Subsequently, samplings of content and form were taken over a period of six months
(June-November 2003) from the 33 MSN local homepages and 23 Yahoo! local
homepages (see Appendix A for the full list of countries). Since six months is
a relatively short period, we focus our analysis on the diversity of local homepages,
and suggest implications concerning their trends mainly to encourage further investigation in this domain.
The content and form elements of the item list that served as a basis for comparison across local homepages followed two main principles: consistency and
remarkableness. Consistency refers to the form and content elements that appear
in all or most local homepages. Thus, it is useful to compare the number of pictures
in different local homepages only if it is a consistent element, that is, it appears in all
or most local homepages. It is less useful to compare elements that are not consistent,
such as the number of banners with sound, which hardly ever appear.
Remarkableness refers to the form and content elements that are most distinguishable and that are referred to as ‘‘cultural markers’’ by Badre (2000). Some form
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1273
elements, such as banners and active (animated) banners, were identified in previous
studies as remarkable form elements (Cyr & Trevor-Smith, 2004; Lo & Gong, 2005;
Würtz, 2005; Zhao et al., 2003); these may further reflect high-context cultures (Hall
& Hall, 1990). Similarly, number of links, number of menus, number of headlines,
search box, and page layout have been identified as remarkable form elements with
distinctive cultural attributes (Barber & Badre, 1998; Callahan, 2005; Cyr & TrevorSmith, 2004).
Based on previous studies of ‘‘cultural markers’’ and our ongoing observations of
MSN and Yahoo!, we identified 10 form elements for examination: number of
frames, number of banners, number of active banners, number of background colors, number of photos, number of main links (headline links), number of links in
general, size of search box, number of menus, and number of pop up windows. Each
one of these elements was further operationalized in detail; thus, for example, the
number of pictures is the number of any graphics above 40 pixels. Although one
researcher conducted the coding, the detailed operationalization of each element
helped to maintain the consistency of the coding process.
Measuring content quantitatively is often a less straightforward process. Here we
focus on topical classification of seven categories: news, economics, entertainment,
sports, shopping, technology, and general information. These topics were chosen due
to their high frequency of appearance in all local homepages. Classifying content by
topics was a natural choice also because both MSN and Yahoo! use topical classification to differentiate graphically and conceptually among different kinds of content.
Excluding rare exceptions, most content could be sorted into those seven categories. Each category had structured and detailed rules regarding the inclusion of
content in it. For example, links to purchase products and services would be categorized under the ‘‘shopping’’ category. A particular challenge was to define the rules
of inclusion and exclusion for the category ‘‘news,’’ which can be relevant for many
different topics, such as economics or sports. In order to maintain the consistency of
the classification process, it was decided to count as news only content that deals with
politics and society in general.
All local homepages were translated by means of online dictionaries into English.
Since local homepages in MSN and Yahoo! consist of very short sentences and are often
already graphically divided into topics, the classification of content into the seven
broad categories was straightforward. Additionally, a research student was employed
to validate the online translation of the Japanese, Chinese, and Korean homepages.
Apart from the general number of links from each category, content was further
subdivided by its location and function. Thus content variables could be, for example, the number of news, economics, or sports headlines, or the number of entertainment or shopping banners (see Appendix B for the full item list).
To conclude, 44 different attributes of content and form were analyzed monthly
over a period of six months in 33 countries for MSN and 23 countries for Yahoo!.
In order to explore the diversity of content and form, three indices were developed
(General Diversity Index, Difference Diversity Index, and National Similarity Index)
1274Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
and a structured statistical analysis was employed (factor and cluster analyses). Both
indices and statistical analyses examined the diversity of local homepages of the same
parent site and its trends over time; thus they complemented and supported each
other.
Three Diversity Indices
The first index, the General Diversity Index (GDI), was designed to explore the
diversity of the content and form of local homepages. It is based on calculating
the coefficient of variation of the form and content variables through three steps:
1. Compute the average and standard deviation across all homepages for each independent variable.
2. Compute the scattering index of the variable (standard deviation/average), also
known as the coefficient of variation.
3. The first index, the GDI, is derived from the average scattering index of the
variables of form and content separately.
Table 1 demonstrates how to calculate the GDI index for a partial sample taken
from actual observations of MSN in June 2003.
The second index, the Difference Diversity Index (DDI), was designed to explore
the diversity of the absolute differences between local homepages and the parent U.S.
homepage. Similar to the GDI, it is based on calculating the coefficient of variation
through the following steps:
Table 1 First index (GDI)—Sample from MSN, June 2003
Country
Banners
Active Banners
Background Colors
Pictures
U.S.
Arabia
Italy
Netherlands
Norway
Spain
U.K.
Brazil
Canada (English)
Mexico
India
Korea
Singapore
Australia
Taiwan
0
2
0
2
2
5
3
2
0
6
3
1
4
1
4
0
2
0
1
1
0
1
2
0
2
3
1
2
0
2
4
4
5
3
4
3
4
4
4
3
5
4
4
3
4
6
8
8
15
14
9
6
8
6
12
4
10
7
5
0
Average
Standard Deviation
Scattering Index
2.33
1.84
0.79
1.13
0.99
0.87
3.87
0.64
0.17
7.87
3.85
0.49
0.58
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1275
1. Compute the absolute differences between each local homepage and the U.S.
homepage for each observation.
2. Compute the average and the standard deviation among all homepages for each
independent variable.
3. Compute the scattering index of the variable (standard deviation/average), also
known as the coefficient of variation.
4. The second index, the DDI, is derived from the average scattering index of the
variables of form and content separately.
A trend of decline in the second index does not indicate that the local homepages
become similar to the U.S. homepage. It only indicates that the absolute differences
become more homogenous. The full meaning of the second index will be further
discussed in the analysis of the results.
The first and the second indices engender a dimensionless number, which is
meaningful only if compared over a period of time to track diversity trends. Since
the calculation of indices is based on the coefficient of variation, it can be implemented easily in other fields to explore the scattering level and its trends.
The third index, the National Similarity Index (NSI), is different from the first
two in the sense that it does not describe the level of diversity among all local
homepages of the same parent site, but rather indicates the level of similarity of each
local homepage to the parent U.S. homepage (MSN or Yahoo!). The steps to calculate the third index are as follows:
1. Compute the ratio between each local homepage and the U.S. homepage for each
observation.
2. If the ratio is greater than 1, use the reciprocal value (absolute ratio), so that it will
be possible to intersect the ratio’s average per each local homepage.
3. The third index, the NSI, is derived from the average of those ratios among all
independent variables for each local homepage.
Table 2 demonstrates how to calculate the third index for a partial sample taken
from actual observations of MSN, June 2003.
The third index indicates the percentage of similarity for each local homepage to
the U.S. homepage. The NSI value ranges from 0 to 1, where a value of 0 indicates
a large difference from the U.S. homepage, while a value of 1 designates the highest
possible similarity to the U.S. homepage. The NSI applies to both form and content
attributes.
Factor and Cluster Analyses
In addition to the three indices, we use statistical analysis to validate and support the
new metrics of indices and to examine the scatter of local homepages in detail. This
was performed through a sequence of three stages:
1. Factor analysis was used to identify correlated variables and replace them with
fewer components that explain the content and form.
1276Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Table 2 Third index (NSI)—Sample from MSN, June 2003
Country
U.S.
Arabia
Italy
Netherlands
Norway
Spain
U.K.
Brazil
Canada (English)
Mexico
India
Korea
Singapore
Australia
Taiwan
Background Color
Absolute Ratio
Picture
Absolute
Ratio
Menu
Absolute
Ratio
Search Box
Size Absolute
Ratio
Average
1.00
1.00
0.80
0.75
1.00
0.75
1.00
1.00
1.00
0.75
0.80
1.00
1.00
0.75
1.00
1.00
0.75
0.75
0.40
0.42
0.67
1.00
0.75
1.00
0.50
0.67
0.60
0.86
0.83
0.00
1.00
0.88
0.91
0.88
0.85
0.95
0.94
0.91
0.91
0.68
0.88
1.00
0.95
0.73
0.88
1.00
0.74
0.80
0.88
0.97
0.74
0.80
0.88
0.81
0.76
0.82
0.72
0.76
0.46
0.74
1.00
0.84
0.82
0.73
0.81
0.78
0.94
0.89
0.93
0.67
0.79
0.83
0.89
0.69
0.66
Average
0.80
2. Cluster analysis was used in order to group local homepages according to similar
characteristics. The homepages in each cluster share common factors of content
or form. The distance between clusters can be measured either by the least squares
method, or by the Ward method based on variation analysis. The Ward (1963)
method was found more adequate for this study, as will be later argued.
3. The common factors in each cluster were traced. Since the clustering process was
based on the new components that the factor analysis generated, we could indicate the common factors of homepages in the same cluster.
All stages of the diversity analysis were carried out each month for six months on
each site for the content and form variables separately, thus enabling us also to
construct a trend component to the study. The observation item list contained
44 variables (10 of form, 34 of content) that were sampled over 332 homepages
(33 MSN 1 23 Yahoo! 3 6 months). Consequently, 14,608 observations were collected.
Results
Analysis of the Three Indices
General Diversity Index (GDI)
Figure 1 does not indicate a clear trend in the general diversity of local homepages.
However, interestingly, form and content have similar trends in MSN, and in October,
the homepages were relatively more similar to each other. If October is regarded as
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1277
Figure 1 MSN GDI trends
an exception, it is possible to observe a slight increase in the general diversity level
both in form and content. The sampling covered a relatively short period, however;
thus a further statistical investigation is required to support this trend.
Similarly, it is difficult to trace general trends in the diversity of local homepages
in Yahoo! over the observation period. Figure 2 indicates that form and content have
different trends in Yahoo!. The best-fit line of the GDI in the content only implies
a slight trend of decline. Although six months may be a relatively short period to
draw a conclusion about the GDI trends in MSN and Yahoo!, those slight trends will
gain further support by the other indices and the statistical analysis and therefore are
worth mentioning.
Difference Diversity Index (DDI)
The second index describes the level of homogeneity of the absolute differences
between the sampled homepages and the main U.S. homepage.
Figure 3 portrays the trends of the DDI in MSN, indicating a general trend of
decline mainly in content. This suggests that the absolute differences became similar
to each other. In Yahoo! it was difficult to trace a general trend for the DDI, and
again content and form had opposite trends. The main power of the DDI is shown
when it is compared with the first index (GDI), as demonstrated in the following
example.
In this example it is assumed that in month A there were 10 pictures in each
homepage (including the U.S. homepage), except for one local homepage that had
Figure 2 Yahoo! GDI trends
1278Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Table 3 Comparison of the first and the second indexes (GDI and DDI)
Month A
Homepage 1
Homepage 2
Homepage 3
Homepage 4
Homepage 5
Average
Standard Dev.
Month B
Number of
Pictures
Absolute
difference
Number of
Pictures
Absolute
difference
10
10
5
10
10
9
2
0
0
5
0
0
1
2
5
10
5
10
10
8
2.4
5
0
5
0
0
2
2.4
GDI = 0.22
DDI = 2
GDI = 0.3
DDI = 1.2
Figure 3 MSN DDI trends
only five pictures in its homepage. Assuming that in the next month another local
homepage had five pictures, the first index increased, while the second index decreased.
This indicates that some homepages become similar to one another, but different
from the U.S. homepage. This phenomenon is called in this research ‘‘the alternative
block,’’ since homepages that become similar to one another suggest alternatives to
the form and content of the U.S. homepage.
Comparing the trends of the first and the second indices therefore indicates that
the alternative block in MSN is getting stronger over the period of six months. In
other words, localization forces appear to be stronger than globalization forces. This
phenomenon will receive further support from the cluster analysis.
In Yahoo! the trends of the first and the second indices are similar during five out
of the six months both in form and content variables, and therefore there is no
reason to discuss the alternative block and its trends.
National Similarity Index (NSI)
The third index indicates the degree of proximity (similarity) of local homepages to
the U.S. homepage in terms of form and content. Its value ranges from 0 (least
similarity) to 1 (greatest similarity).
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1279
Figure 4 MSN—Trends of the NSI
Figure 4 portrays the trends of the third index over a period of six months in
MSN. It indicates that there was a general trend of decline in form and content,
which means that local homepages become more different from the U.S. homepage
in terms of form and content over a period of six months. These findings are
consistent with the trends of the first index that implied an increase of heterogeneity
and with the growth of the alternative block that the second index revealed.
Figure 5 shows that in Yahoo!, unlike in MSN, the NSI increases in content only.
There are no clear trends in form in the period of the observation, although it might
be suggested that the content of local homepages in Yahoo! becomes more similar to
the main U.S. homepage. These findings conform to the trend of homogeneity in
content that the GDI previously suggested.
Another interesting result provided by the third index is the level of similarity of
each homepage to the U.S. homepage. Table 4 summarizes this proximity for MSN,
June 2003, where values close to 1 indicate great similarity and values close to
0 indicate great difference from the U.S. homepage.
Interestingly, Table 4 (June 2003) and the results for the next five months (JulyDecember 2003) display the same patterns over a period of time for form and
content attributes. Local homepages in MSN that were similar to the U.S. homepage
in form (e.g., the U.K., Canada, Germany, Belgium, and France) were often similar in
content as well. Local homepages in MSN that were different from the U.S. homepage in form (e.g. China, Slovakia, South Africa, Finland, Denmark, The Czech
Republic, Austria, and Switzerland) were often different in content as well. A further
analysis will reveal the reasons behind those trends.
Figure 5 Yahoo!—Trends of the NSI
1280Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Table 4 NSI in MSN, June 2003
Ranking Form Diversity (MSN)
Ranking Content Diversity (MSN)
1
U.S.
0.819 India
1
U.S.
0.466 Belgium (French)
0.937 Canada
0.810 Hong Kong
0.707 Netherlands 0.461 Norway
0.914 Germany
0.805 Spain
0.701 U.K.
0.45 Korea
0.908 Brazil
0.759 Taiwan
0.701 Japan
0.427 Sweden
0.888 Malaysia
0.746 Australia
0.673 Arabia
0.423 Spain
0.882 France
0.736 Sweden
0.669 Germany
0.403 Hong Kong S.A.R.
0.874 U.K.
0.726 Israel
0.641 Canada
0.361 Taiwan
0.873 Italy
0.683 Denmark
0.606 France
0.354 Austria
0.866 Latin America 0.668 Czech Republic 0.598 Italy
0.352 Czech Republic
0.865 Korea
0.659 New Zealand 0.593 Brazil
0.337 Singapore
0.861 Belgium
0.642 Mexico
0.554 New Zealand 0.28 India
0.86 Norway
0.519 Switzerland
0.554 Israel
0.279 Denmark
0.852 Arabia
0.499 China
0.536 Latin America 0.249 Switzerland (German)
0.846 Japan
0.495 Finland
0.519 Malaysia
0.187 Finland
0.842 Netherlands 0.467 South Africa 0.498 Australia
0.118 South Africa
0.840 Singapore
0.463 Austria
0.492 Mexico
0
China
In Yahoo! it was difficult to find a pattern over time. There was no significant
consistency in homepage ranking order for form or content.
Results of the Statistical Analysis
Factor Analysis
In addition to the three indices, statistical tools were exploited to further analyze the
factors behind the diversity of the homepages’ form and content. By means of
principal component analysis the correlated variables were extracted and a linear
combination that could explain them was found.
Table 5 displays the percentage of explained variation accounted for by the new
components. Each of the four new components represents a group of correlated
variables. The first component represents the ‘‘number of links,’’ the ‘‘number of
main links,’’ and the ‘‘number of menus.’’ Those highly correlated variables together
comprise the form of the content. Similarly, the second new component represents the
‘‘size of the search box,’’ the ‘‘number of background colors,’’ and the ‘‘number of
frames,’’ which together comprise the page layout or the pattern. The third component represents the ‘‘number of pop-up windows’’ and the ‘‘number of active banners,’’ which together comprise the activity. Finally, the fourth component represents
the ‘‘number of photos’’ and ‘‘number of banners’’ that comprise colorfulness. Apparently, each month the same form variables were consistently correlated and grouped
into the same new components that comprise four aspects of the form: form of
content, patterns, activity, and colorfulness. Those components will be used later
for the cluster analysis.
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1281
Table 5 New form components—MSN, June 2003
Note: Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
a. Rotation converged in 6 iterations.
In Yahoo! the factor analysis of the form shows similar patterns. The only
difference is that local homepages in Yahoo! are more similar to one another. The
variable ‘‘number of background colors,’’ for instance, always gets the value of 4, and
there were hardly any pop-up windows. This is why the factor analysis process in
Yahoo! generates only three new components that describe three aspects of the form
(the colorfulness and activity variables were reduced into one factor). Those three
new components appeared consistently in all six months with no variation.
The factor analysis for content was less consistent. The correlation matrix showed
some unreasonable relations among the 34 independent variables. The unreasonable
relations appeared mostly within variables that usually get a zero value and therefore
create ‘‘noise’’ (e.g., the ‘‘number of sports banners’’). After filtering those variables,
the correlation matrix of the 20 content variables that were left made much more
sense.
Table 6 presents the new groups of correlated variables after filtering the variables that create ‘‘noise.’’ The variables in each group are reasonably correlated, since
they deal mostly with the same subject. Interestingly, the variables that deal with
economics and shopping were highly correlated in almost every month and therefore
were replaced by a single new component. This may indicate that MSN content
editors in many countries have similar attitudes and preferences as regards those
particular topics. Entertainment does not attain representation as an independent
component, but rather it is reflected in some components in combination with other
issues.
Unlike the factor analysis of form, the factor analysis of content in both MSN and
Yahoo! creates slightly different groups of variables for each month. Variables of the
same subject were almost always correlated and therefore were replaced by a single
new component.
1282Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Table 6 New content components—MSN, June 2003
Notes: Extraction Method: Principal Component Analysis.
Rotation Method: Varimax with Kaiser Normalization.
Cluster Analysis and Tracing the Factors
The cluster analysis is the second stage in the diversity analysis process. It uses the
factor analysis components as input and groups together local homepages with
similar patterns of form and content.
Figure 6 delineates the results of a cluster analysis of form in MSN, June 2003.
The horizontal axis shows the distance between each cluster using the Ward method
(Ward, 1963). This method was found to be most adequate, since it creates a small
number of clusters with relatively more homepages. We decided to focus on clusters
whose distance was between 5 and 10 units from each other, entailing six main
clusters. In this way, we could trace the common factors for all homepages within
the same cluster and observe the trends of those six clusters each month.
Figure 6 and Table 7 show that the U.S. homepage was located in the biggest
cluster (no. 1) and that MSN Israel was located in a separate cluster (no. 6). This is
because the form of MSN Israel is significantly different from the form of other local
homepages in MSN. Homepages that have relatively less content and therefore
a simple form, like MSN Austria and Finland, are located together in the same cluster
(no. 3).
Figure 7 displays screenshots of four representative local homepages in MSN. It
clearly indicates that MSN U.S. and MSN Canada, which are also located in the same
cluster (no. 1), have very similar page layouts as well as a number of background
colors and photos. By contrast, MSN Israel has a very different design and a greater
number of photos. Finally, MSN Finland has a relatively simple layout and less
content.
Table 7 shows how the composition of each form cluster varies over time in
MSN. It shows that the biggest cluster contains MSN U.S., together with other
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1283
Figure 6 Form cluster analysis—MSN, June 2003
1284Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1285
July 2003
Patterns, Form
of Content
U.S.
Arabia
Belgium
France
Germany
Italy
Netherlands
Norway
Spain
Sweden
United K
Brazil
Canada
Latin Am
Japan
India
Korea
Malaysia
Taiwan
June 2003
Patterns, Form
of Content
U.S.
Arabia
Belgium
Czech Re
France
Italy
Netherlands
Norway
Spain
United K
Brazil
Canada
Latin Am
India
Japan
Korea
Malaysia
Singapore
U.S.
Italy
Spain
Sweden
United K
Latin Am
China
Japan
Malaysia
Singapore
Taiwan
Patterns
August 2003
Table 7 MSN Form clusters and common factors over time
Patterns, Form
of Content
U.S.
Belgium
France
Italy
United K
Brazil
Canada
Latin Am
Japan
Korea
Taiwan
September 2003
Patterns, Colorfulness,
Form of Content
U.S.
Belgium
France
Netherla
Norway
Spain
Sweden
United K
Brazil
Canada
Latin Am
Japan
Singapore
Taiwan
October 2003
(continued)
Form of Content,
Patterns,
U.S.
Belgium
France
United K
Brazil
Canada
Latin
India
Japan
Korea
Singapore
Taiwan
November 2003
1286Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Poor Form
Austria
Finland
Switzerland
South Africa
Patterns, active
Czech Re
Denmark
Mexico
China
Singapor
Poor Form
Austria
Finland
Switzerland
South Africa
Patterns, active
Denmark
Sweden
Mexico
China
Colorfulness, active Active, Patterns
Germany
Hong Kong
Hong Kong
Taiwan
July 2003
Continued
June 2003
Table 7
Active, Patterns
Arabia
Denmark
Germany
Mexico
Colorfulness
Netherlands
Norway
Poor Form
Austria
Czech Re
Finland
Slovakia
Switzerland
South Africa
August 2003
Active
Arabia
Germany
Norway
Mexico
Patterns
Denmark
Netherla
Spain
Sweden
China
India
Poor Form
Austria
Czech Re
Finland
Slovakia
Switzerland
South Africa
September 2003
Poor Form
Austria
Czech Re.
Finland
Slovakia
Switzerland
Latin Am.
China
Malaysia
South Africa
November 2003
Active, Patterns
Arabia
Denmark
Germany
Italy
Active
Arabia
Germany
Hong Kong
(continued)
Patterns, Colorfulness, active Colorfulness, Patterns
Mexico
Denmark
China
Italy
Netherlands
Norway
Spain
Sweden
Mexico
Poor Form
Austria
Czech Re
Finland
Slovakia
Switzerland
South Africa
October 2003
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1287
Hong Kong
Singapore
Hong Kong
India
Korea
Hong Kong
India
Korea
Malaysia
October 2003
Colorfulness, active
November 2003
Form of Content
Australia
New Zealand
Form of Content
Belgium
France
Brazil
Canada
Australia
New Zeal
Form of Content Form of Content
Australia
ustralia
New Zealand
New Zealand
Form of Content
Australia
New Zealand
September 2003
August 2003
Form of Content
Australia
New Zealand
July 2003
Israel
Continued
Colorfulness, active, Colorfulness,
Colorfulness, active, Colorfulness,
Colorfulness, active,
Form of Content
active, Form of Content Form of Content
Form of Content Form of Content
Israel
Israel
Israel
Israel
Israel
June 2003
Table 7
countries that appear consistently over the observation period such as the homepages
of the U.K., Brazil, Canada, Italy, Japan, and France. This is consistent with the
analysis of the third index (NSI). The common factor that makes them belong to
the same cluster is the similarity in the pattern of the form (number of frames and
size of the search box). Table 7 indicates that this cluster becomes smaller over
a period of six months (from 19 to 12 homepages), supporting previous findings.
The heterogeneity of local homepages in MSN grows, and they become more different from the U.S. homepage over time.
Another cluster consists of MSN Austria, the Czech Republic, Finland, Slovakia,
Switzerland, and South Africa. The common factor for this cluster is the limited
content and therefore the simple form. This cluster grows over the period of time
(from 4 to 9 homepages). It therefore supports the findings of the second index
(DDI), which indicate the growth of an ‘‘alternative block.’’ The cluster analysis
reveals exactly what this ‘‘alternative block’’ is, and what the variables that make it
distinctive are.
Using the same method, a cluster analysis was employed to analyze the content
diversity of homepages based on the content components in MSN. It was found that
similar to the form clusters, the biggest content cluster contains MSN U.S., together
with the local homepages of the U.K., Brazil, Canada, Japan, and France. This finding
Figure 7 Screenshots of MSN’s local homepages, July 2003
1288Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
is consistent with the analysis of the third index (NSI), in which those countries
ranked first as the most similar to MSN U.S. in both content and form. The common
factor that makes them belong to the same cluster is the relatively frequent appearance
of economics and shopping-related content. Similar to the main form cluster, the main
content cluster shrinks over a period of six months (from 14 to 5 homepages), supporting previous findings. The heterogeneity in content grows as well, and local homepages in MSN become more different from the U.S. homepage over time.
Similarly, cluster analysis was used to explore the diversity of form in Yahoo!’s
local homepages over time. It was found that the biggest cluster contains Yahoo!
U.S., together with the homepages of Asia, Brazil, India, Mexico, and Canada. The
common factor of this cluster is the similarity in the patterns of the content (number
of links and menus). There is no clear trend for this cluster to become smaller or
bigger over time. These findings are consistent with the third index analysis.
Interestingly, the composition of countries in each cluster is consistent over time.
One cluster consists of Yahoo! Catalan only, which provides little content and
therefore has a simple form; another cluster consists of the homepages of Scandinavian countries: Denmark, Sweden, and Norway, all of which have relatively colorful
and active homepages. Another cluster consists of the homepages of European
countries: France, Germany, and Italy, all of which have a relatively high number
of links in their homepages; another cluster consists of the Asian countries homepages: Japan, Hong Kong, and Taiwan, each of which has a relatively small number of
links in their homepages; and finally there is a cluster for Yahoo! China, which has
a relatively colorful, active, and content-full homepage.
The composition of factors was further explored in each content cluster over
time in Yahoo!. It was found that the cluster that contains Yahoo! U.S. has no stable
composition and therefore no stable common factor. The cluster that contains the
U.S. homepage grows over the period of six months (from 2 to 13 homepages). This
supports the results of the first and third indices analyses. The homogeneity in
content increases and the homepages become more similar to the U.S. homepage
over time.
Discussion: Towards A Dictated Heterogeneity?
This article presented new methods, indices, and metrics to explore cultural diversity
online and implemented them to measure the similarities among homepages of MSN
and Yahoo! in a large number of countries over time. The tools and methodology
proved useful in measuring content and form proximities of affiliated websites. Since
previous comparative studies in the field were limited to a small number of countries
and often used Hofstede’s (1997) framework to analyze content and form, we hope
to encourage further use of these new analytical tools and approaches to explore
online trends of heterogeneity and localization on a large scale.
The study posed two main research questions, the first about cultural diversity
online and the second about trends toward homogeneity or heterogeneity over time.
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1289
Despite the relatively short observation period, the findings clearly implied that MSN
tended to increase the customization of form and content in its local homepages.
Additionally, it was found that local homepages in MSN tended to differ from the
U.S. homepage over time in terms of both content and form.
Conversely, Yahoo!’s analysis identified a trend toward homogeneity of content.
The resemblance of the local homepages to the U.S. homepage grew in term of
content. However, in terms of form, the cluster analysis indicated the distinctive
differentiation of local homepages by their region: America, Europe, Scandinavia,
and the Far East. The relatively high activity and colorfulness of Asian homepages
in both MSN and Yahoo! support previous studies, which found similar trends
in websites of transnational corporations and e-businesses as a reflection of
high-context cultures (Becker, 2002; Cyr, Bonanni, Bowes, & Ilsever, 2005; Würtz,
2005).
In general, the hypothesis that assumed trends toward homogeneity was rejected.
MSN, an American brand and popular content provider, displayed heterogeneous
homepages and trends toward localization. These findings may therefore support
similar studies that found cultural heterogeneity and localization of web design and
usability (Badre, 2000; Becker, 2002; Cyr & Trevor-Smith, 2004; Lo & Gong, 2005;
Marcus & Gould, 2000; Sheridan, 2001; Singh & Baack, 2004; Singh, Xhao, et al.,
2003; Singh, Furrer, et al., 2004; Sun, 2001; Tsui & Paynter, 2004; Würtz, 2005;
Zhao et al., 2003). Moreover, our study found a growing diversity of content in
MSN local homepages, suggesting a new perspective for further investigation in the
field.
These trends may be also explained as a result of the business model of MSN that
focuses on direct subscription and production of customized cultural artifacts (Van
Couvering, 2004). Heterogeneity and localization trends do not imply less control
by the parent site over the local sites. On the contrary, these may be analyzed as a
stronger leverage to control users’ preferences. Through addressing local content,
big portals and content providers strengthen their grip on users, attracting
attention that non-American users might not otherwise pay to more global content
and form.
In contrast to MSN, the relative homogeneity in the content of Yahoo!’s local
homepages and their similarity to the U.S. parent site imply that Yahoo! takes less
account of cultural issues. A few studies (Kang & Corbitt, 2001; Schmied, 2003) may
support this trend; they propose a certain level of standardization in websites of transnational (and particularly U.S.-based) corporations. These findings are consistent
with the different business model of Yahoo!, which is based mainly on advertisement
(Van Couvering, 2004) rather than on the provision of customized information
products.
To conclude, the increasing diversity of local homepages in MSN and the
regional division of form clusters in Yahoo! clearly indicate trends of localization
and cultural diversity in cyberspace and a gradual departure from their U.S. sources.
Consequently, we may expect further customization of local homepages, especially in
1290Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
MSN, in the Far East and Latin America, as MSN adds new ethnic cultures to its
customer base. This is probably why during the observation period MSN launched
another homepage entitled ‘‘Latin.’’ This homepage is culture and Spanish-language
oriented, rather than geography oriented.
It may be argued that the customization process of content and form proceeds in
phases, starting with geographical and national distinctions and progressing towards
a focus on ethnographic differences. A reason for that could be that it is technically
easier for a corporation to conduct a geographical customization than an ethnographic and more specific one.
Future research into the increasing customization of local homepages, especially
in popular and influential U.S.-based companies such as MSN and Yahoo!, may
further contribute to the understanding of cultural globalization (Appadurai,
1996; Basch, Schiller, & Blanc, 1994; Foster, 1991; Friedman, 1990). In this sense,
our findings support previous studies that highlighted the centrality of customization and cultural diversity (Anderson, 2006; Caves, 2000; Shapiro & Varian, 1999;
Sunstein, 2001). Additionally, our findings suggest that future studies of this diversity should increasingly focus on ethnographic as well as geographical differences.
Acknowledgments
The research for this article was supported by the faculty of management, Tel Aviv
University. We would like to thank the administration staff, and especially Mrs. Orit
Aviv-Prihed, who helped us to carry out this research. We would like to thank
Dr. Glenn McGregor and Dr. Yaojun Li of Birmingham University for their contribution to designing the methodology of this research. A special thanks to Professor
Robert E.F. Smith for his comments on an earlier version of this article.
Note
1 Information search plays a prominent role in websites such as MSN and Yahoo!, and
therefore the size of the search box was considered a notable element of form (see also
Cyr & Trevor-Smith [2004], who compared the search layout of various national
websites). The size of the search box was measured in pixels and ranged between 140px,
which is relatively small (3.7cm), and 620px, which is relatively large (16.3cm).
References
Adorno, T. W. (1991). The Culture Industry: Selected Essays on Mass Culture. London:
Routledge.
Ahituv, N. (2001). The open information society. Communications of the ACM, 44(6), 48–52.
Anderson, C. (2006). The Long Tail. London: Random House Business.
Appadurai, A. (1996). Diversity and disciplinarity as cultural artifacts. In C. Nelson &
D. P. Gaonkar (Eds.), Disciplinarily and Dissent in Cultural Studies (pp. 23–36).
New York: Routledge.
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1291
Badre, A. N. (2000). The effects of cross-cultural interface design orientation on World Wide
Web user performance. GVE Research Technical Reports. Retrieved June 22, 2007 from
ftp://ftp.cc.gatech.edu/pub/gvu/tr/2001/01-03.html
Bagdikian, B. (2004). The New Media Monopoly. Boston, MA: Beacon Press Books.
Barabási, A. (2001). The physics of the Web. Physics World, 14(7), 33–38.
Barber, W., & Badre A. N. (1998, June).Culturability: The merging of culture and usability. In
Proceedings from the 4th Conference on Human Factors and the Web. Retrieved March 21,
2006 from http://research.microsoft.com/users/marycz/hfweb98/barber/index.htm
Barzilai-Nahon, K. (2006). Gatekeeping, virtual communities, and their gated:
Multidimensional tensions in cyberspace. International Journal of Communications, Law
and Policy, 11, Autumn. Retrieved July 15, 2007 from http://projects.ischool.washington.
edu/karineb/html/pub/IJCLPGatekeeping.pdf
Basch, L. G., Schiller, N. G., & Blanc, C. S. (1994). Nations Unbound: Transnational Projects,
Postcolonial Predicaments, and Deterritorialized Nation-States. Amsterdam: Gordon and
Breach.
Becker, S. A. (2002). An exploratory study on web usability and the internationalization of
U.S. e-business. Journal of Electronic Commerce Research, 3(4), 265–278.
Callahan, E. (2005). Cultural similarities and differences in the design of university websites.
Journal of Computer-Mediated Communication, 11(1), article 12. Retrieved July 15, 2007
from http://jcmc.indiana.edu/vol11/issue1/callahan.html
Castells, M. (1996). The Information Age: Economics, Society and Culture (Vol. 1.): The Rise of
the Network Society. Oxford: Basil Blackwell.
Caves, R. (2000). Creative Industries: Contracts between Art and Commerce. Cambridge:
Harvard University Press.
Cyr, D., Bonanni, C., Bowes, J., & Ilsever, J. (2005). Beyond trust: Website design preferences
across cultures. Journal of Global Information Management, 13(4), 24–52.
Cyr, D., & Trevor-Smith, H. (2004). Localization of web design: An empirical comparison of
German, Japanese, and United States web site characteristics. JASIST, 55(1), 1199–1208.
DiMaggio, P., Hargittai, E., Neuman, W. R., & Robinson, J. P. (2001). Social implications of
the Internet. Annual Review of Sociology, 27, 307–336.
Foster, R. J. (1991). Making national cultures in the global ecumene. Annual Review of
Anthropology, 20, 235–260.
Friedman, J. (1990). Being in the world: Globalization and localization. In M. Featherstone
(Ed.), Global Culture: Nationalism, Globalization and Modernity (pp. 311–328).
London: Sage.
Global Reach. (2004). Global Internet statistics: Sources & references. Retrieved June 22, 2007
from http://global-reach.biz/globstats/refs.php3
Hall, E. T., & Hall, M. R. (1990). Understanding Cultural Differences. Yarmouth, ME:
Intercultural Press Inc.
Hofstede, G. (1997). Cultures and Organizations: Software of the Mind. New York:
McGraw-Hill.
Kang, K. S., & Corbitt, B. (2001). Effectiveness of graphical components in web site
e-commerce application: A cultural perspective. The Electronic Journal Systems in
Developing Countries, 7(2), 1-6. Retrieved September 22, 2006 from http://
www.ejisdc.org/ojs/include/getdoc.php?id=35&article =35&mode=pdf
Kellerman, A. (2002). The Internet on Earth: A Geography of Information. London: Wiley.
1292Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Lash, S. (2002). Critique of Information. London: Sage.
Leonardi, P. M. (2002). Cultural variability in web interface design: Communicating U.S.
Hispanic cultural values on the Internet. In F. Sudweeks & C. Ess (Eds.), Proceedings of
Cultural Attitudes towards Communications and Technology (pp. 297–315). Murdoch,
Australia: Murdoch University.
Lo, B. W. N., & Gong, P. (2005). Cultural impact on the design of e-commerce websites:
Part I: Site format and layout. Issues in Information Systems, VI(2), 182–189. Retrieved
March 7, 2006 from http://www.jcis-online.org/iis/2005_IIS/PDFs/Lo_Gong.pdf
Marcus, A., & Gould, E.W. (2000, June). Cultural dimensions and global web user-interface
design: What? So what? Now what? In Proceedings from the 6th Conference on Human
Factors and the Web. Retrieved March 5, 2006 from http://www.amanda.com/resources/
hfweb2000/AMA_CultDim.pdf
Mattelart, A. (1991). Advertising International: The Privatization of Public Space. London:
Routledge.
Neuman, W. R., McKnight, L. W., & Solomon, R. J. (1998). The Gordian Knot: Political
Gridlock on the Information Highway. Cambridge: MIT Press.
Nielsen/NetRatings. (2004). Audience measurement service. Retrieved March 17, 2004 from
http://www.nielsen-netratings.com/press.jsp?section=pr_netv&nav=3
Norris, P. (2004). The bridging and bonding role of online communities. In P. N. Howard &
S. Jones (Eds.), Society Online: The Internet in Context (pp. 31–43). Thousand Oaks,
CA: Sage Publications.
Robbins, S. S., & Stylianou, A. C. (2003). Global corporate websites: An empirical
investigation of content and design. Information and Management, 40(3), 205–212.
Schmied, J. (2003). Cultural discourse in Internet business. In E. H. Oleksy &
B. Lewandowska-Tomaszczyk (Eds.), Research and Scholarship in Integration Processes:
Poland-USA-EU (pp. 273–283). Lodz: Lodz U.P.
Shapiro, C., & Varian, H. (1999). Information Rules: A Strategic Guide to the Network
Economics. Boston: Harvard Business School Press.
Sheridan, E. F. (2001). Cross-cultural web design: Considerations for developing and
strategies for validating locale appropriate on-line content. Multilingual Computing &
Technology, 12(7), 53–56.
Shils, E. (1963). The theory of mass society. In P. O. Glencoe (Ed.), America as a Mass Society
(pp. 30–50). Glencoe, IL: Free Press.
Singh, N., & Baack D. W. (2004). Web site adaptation: A cross-cultural comparison of U.S.
and Mexican web sites. Journal of Computer-Mediated Communication, 9(4). Retrieved
September 20, 2006 from http://jcmc.indiana.edu/vol9/issue4/singh_baack.html
Singh, N., Furrer, O., & Ostinelli, M. (2004). To localize or standardize on the Web: Empirical
evidence from Italy, India, Netherlands, Spain, and Switzerland. Multinational Business
Review, 12(1), 69–87.
Singh, N., Xhao, H., & Hu, X. (2003). Cultural adaptation on the Web: A study of American
companies’ domestic and Chinese websites. Journal of Global Information Management,
11(3), 63–80.
Sun, H. (2001). Building a culturally-competent corporate web site: An explanatory study of
cultural markers in multilingual web design. In Proceedings from SIGDOC 2001
(pp. 95–102). Retrieved June 22, 2007 from http://delivery.acm.org/10.1145/510000/
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1293
501536/p95-sun.pdf?key1=501536&key2=2727352811&coll=GUIDE&dl=GUIDE&
CFID=22084028&CFTOKEN=51919415
Sunstein, C. (2001). Republic.com. Princeton: Princeton University Press.
Tsui, T. W. C., & Paynter, J. (2004). Cultural usability in the globalisation of news portal.
Lecture Notes in Computer Science, 3101, 501–510.
Van Couvering, E. (2004, July). New media? The political economics of Internet search
engines. In Proceedings from the Annual Conference of the International Association of
Media & Communications Researchers, Porto Alegre, Brazil.
Ward, J. H., Jr. (1963). Hierarchical grouping to optimize an objective function. Journal of the
American Statistical Association, 58(301), 236–244.
Waxman, J. (2000). The Old 80/20 Rule Takes One on the Jaw. Internet Trend Report 1999,
Review. San Francisco: Alexa Research.
Würtz, E. (2005). A cross-cultural analysis of websites from high-context cultures and
low-context cultures. Journal of Computer-Mediated Communication, 11(1), article 13.
Retrieved May 15, 2006 from http://jcmc.indiana.edu/vol11/issue1/wuertz.html
Zhao, W., Massey, B. L., Murphy, J., & Liu, F. (2003). Cultural dimensions of website design
and content. Prometheus, 21(1), 75–84. Retrieved March 7, 2006 from http://
web.biz.uwa.edu.au/staff/jmurphy/Cultural_Dimensions.pdf
Appendix A
Table 8 Full list of local homepages in MSN and Yahoo!
MSN
U.S.
Canada (English)
Japan
Brazil
Israel
Latin America
France
Belgium (French)
Germany
Spain
United Kingdom
Singapore
Australia
New Zealand
Norway
Arabia
Netherlands
Yahoo!
Sweden
Italy
Malaysia
Korea
Taiwan
India
Mexico
Hong Kong S.A.R.
Denmark
Czech Republic
South Africa
Switzerland (German)
Austria
Finland
Slovakia
China
Sweden
U.S.
U.K. & Ireland
Australia & NZ
France
Brazil
Germany
Argentina
Norway
Hong Kong
Denmark
Taiwan
Mexico
Sweden
Asia
Japan
Singapore
India
Italy
Korea
Canada
Spain
Catalan
China
1294Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Appendix B
Table 9 Full list of content and form elements
Content
Form
News
Main (headline) News
Local News
News Banner
Keyword News*
Economics
Main (headline) Economics
Local Economics
Economics Banner
Keyword Economics*
Entertainment
Main (headline) Entertainment
Local Entertainment
Entertainment Banner
Keyword Entertainment*
Sport
Main (headline) Sport
Local Sport
Sport Banner
Keyword Sport*
Shopping
Main (headline) Shopping
Shopping Banner
Keyword Shopping*
Technology
Main (headline) Technology
Technology Banner
Keyword Technology*
General Information
Main General Info.
General Info. Banner
Keyword General Info.*
Study English
Keyword Study English*
Frames
Banners
Active
Banners
Background Colors
Photos
Main Links
Links
Search Box Size
Menus
Note: *Within the top popular search queries
Appendix C
Table 10 Top 10 parent companies worldwide (Home Panel February 2004)
Parent Name
UniqueAudience (000)
Reach %
Time Per Person
United States
Microsoft
Time Warner
Yahoo!
93,672
82,530
79,603
66.25
58.37
56.30
01:32:48
03:59:38
01:57:25
France
Microsoft
Wanadoo
Google
Iliad - Free
Time Warner
Yahoo!
9,190
8,624
6,591
5,995
4,635
4,333
66.68
62.58
47.82
43.50
33.63
31.44
02:09:19
00:50:20
00:23:13
00:27:30
02:50:51
00:42:34
Hong Kong
Yahoo!
2,068
76.61
01:41:05
(continued)
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1295
Table 10
Continued
Parent Name
UniqueAudience (000)
Reach %
Time Per Person
Microsoft
1,964
72.75
01:34:02
Spain
Microsoft
Google
Terra Lycos
Wanadoo
Yahoo!
6,460
5,231
3,161
3,142
2,935
77.54
62.79
37.94
37.71
35.23
04:30:54
00:27:14
00:23:26
00:23:09
00:38:01
3,423
1,827
1,553
1,400
1,315
1,309
1,213
74.27
39.64
33.70
30.37
28.54
28.41
26.32
01:50:05
00:48:11
00:15:42
00:20:14
00:24:02
00:15:38
00:47:08
1,093
23.71
00:12:19
United Kingdom
Microsoft
Google
Yahoo!
14,652
9,762
7,899
69.92
46.59
37.70
02:05:05
00:18:31
01:01:50
Switzerland
Microsoft
Google
Bluewin
Yahoo!
2,163
1,630
1,501
794
71.90
54.18
49.87
26.37
01:24:03
00:20:37
00:39:06
00:49:27
Sweden
Microsoft
Aftonbladet Hierta
Eniro
TeliaSonera
Bonnierförlagen
Google
Förenings
Sparbanken
Yahoo!
Source: Nielsen//NetRatings, retrieved May 13, 2004 (http://www.nielsen-netratings.com).
Note: The data about the popularity of MSN and Yahoo! were retrieved near the observation
period. For more recent statistics, see http://www.nielsen-netratings.com.
About the Authors
Elad Segev is a doctoral candidate at Keele University, a lecturer of Media and
Communications at Aston University, and a former research student at Tel Aviv
University in the Faculty of Management. His research deals with technology in
general and the Internet in particular, and its social, political, and cultural
implications.
Webpage: http://www.eladsegev.com
Address: School of Politics, International Relations and Philosophy (SPIRE), Keele
University, Keele, Staffordshire ST5 5BG, UK
1296Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association
Niv Ahituv is the Marko and Lucie Chaoul Chair for Research in Information
Evaluation and the Academic Director of the Institute of Internet Studies of Tel
Aviv University. His research deals with information economics, information system
strategy and management, and social and business implications of the Internet.
Webpage: http://recanati.tau.ac.il/Index.asp?ArticleID=76&CategoryID=164
Address: Faculty of Management, Tel Aviv University, Tel Aviv, 69978, Israel
Karine Barzilai-Nahon is Assistant Professor in the Information School at the University of Washington. Formerly she held senior positions in Research and Development in hi-tech industry. Her research deals with social and business aspects of the
Internet and telecommunications.
Webpage: http://projects.ischool.washington.edu/karineb/
Address: The Information School, University of Washington, Mary Gates Hall,
Seattle, WA 98195, USA
Journal of Computer-Mediated Communication 12 (2007) 1269–1297 ª 2007 International Communication Association1297