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This article explores the relationship between national culture and computer-mediated communication (CMC) in Wikipedia. The articles on the topic game from the French, German, Japanese, and Dutch Wikipedia websites were studied using content analysis methods. Correlations were investigated between patterns of contributions and the four dimensions of cultural influences proposed by Hofstede (Power Distance, Collectivism versus Individualism, Femininity versus Masculinity, and Uncertainty Avoidance). The analysis revealed cultural differences in the style of contributions across the cultures investigated, some of which are correlated with the dimensions identified by Hofstede. These findings suggest that cultural differences that are observed in the physical world also exist in the virtual world.
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The Internet and the World Wide Web enable people from different geographical locations to communicate with one another, share information, and build commercial or interest-based relationships and personal friendships (Cummings, Butler, & Kraut, 2002; Preece & Maloney-Krichmar, 2005). Different kinds of communities emerge due to this possibility, some of which carry over from the virtual to the physical world (Preece & Maloney-Krichmar, 2005). Preece and Maloney-Krichmar (2005) define online community as communication among a group of people “who come together for a particular purpose, and who are guided by policies (including norms and rules) and supported by software” (n.p., emphasis original). That is, online communication takes place with the help of various tools—such as email, chat, newsgroups, message boards, and more recently blogs and wikis—that make it possible for people to communicate beyond their national borders.
The focus of this study, wiki technology, was designed by Ward Cunningham in 1995 as a tool for collaborative work (Cunningham & Leuf, 2001; Guzdial, Rick, & Kehoe, 2001). Collaboration is defined as working together to achieve collective results that the participants would be incapable of accomplishing working alone (Wikipedia, 2006a). Wikis offer a way to work collaboratively to create web content that is usually created by individuals; as such, they facilitate new ways of social collaboration online (Zaphiris, Ang, & Laghos, in press). Collaborating participants are those who contribute actively to the wiki site. In a wiki site, each contributor can revisit the pages he or she has edited and check the progress of the site. Thus, wiki collaborations are characterized by the sharing of knowledge whenever it is needed and wherever it is located (Lipnack & Stamps, 1997); this is a primary characteristic of computer-supported collaborated work (CSCW).
Although the Internet is a global medium, its users and creators have different backgrounds, live in different environments, and belong to different cultures. Different styles of computer-mediated communication (CMC) among members of different cultures can lead to misunderstandings and problems in communication. Differences in the standards for writing time, dates, addresses, and numbers can also cause confusion; the same goes for differences in symbols, colors, and metaphors. Even a particular style of writing may be considered friendly in one culture and offensive in another (Stengers, De Troyer, Mushtaha, Baetens & Boers, 2004). It is therefore important to study how people from different cultures behave in CMC, such as how they choose representations and how they work together and govern themselves. This can lead to a better understanding of how cultural diversity is spread in online communities and help an Internet user approach users from different cultures in ways that are appropriate to their cultural backgrounds.
This study aims to explore the relatively new research area of cultural differences in wikis through the use of content analysis methods to investigate the behavior of wiki participants. The primary focus of the study is the relations between the patterns of changes on wiki sites and the cultural backgrounds of the contributors. Content analysis methods have been used previously to study wikis (Emigh & Herring, 2005), and the influence of cultural background on web design has also been explored (Callahan, 2005). However, as far as we know, there has been no previous study that combined these two areas to apply content analysis methods to the study of cultural influences on wiki collaborations. Specifically, we investigate the relation between users’ behavior in Wikipedia and their cultural backgrounds as defined by the cultural dimensions proposed by Hofstede (1991).
Wikipedia is a purely online encyclopaedia that is implemented through wiki technology and that aims to build information and consensus among community members about different topics. However, as Wikipedia exists in different languages, differences in the creation of articles across the language versions might occur. An article is developed by modifying the current state of a page through changing the content or adding or deleting information. Since these changes can be tracked and examined, Wikipedia provides a good source of information for investigating cultural differences in CMC.
The following section presents an overview of wiki technology and Wikipedia, cultural issues, and previous research in these areas. The methodology of our investigation is then described. The main question that we address is: How, if at all, do differences in the cultural backgrounds of Wikipedia contributors influence their behavior? An analysis of all edit operations performed on the French, German, Japanese, and Dutch Wikipedia pages about the topic game shows that there are correlations between Hofstede’s cultural dimensions and the nature and frequency of specific edit operations made by contributors.
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The French article about game included 228 versions, the German article 155 versions, the Japanese article 70 versions, and the Dutch article 47 versions. In total, 952 changes were analyzed. Additional recorded data were the name/IP address of the user and the date of the edit. From these the number of contributors was extracted (see Table 2). The large number of contributors supports the assumption that the measured behavior does not reflect the work of just a few individuals.
Table 2. Percentage of changes in each category and each language
| ||French page||German page||Japanese page||Dutch page|
|Total no. of changes||424||309||127||92|
|No. of contributors||109||80||42||32|
Table 2 shows the percentage of changes that fell under each of the 13 categories for each language version.
A Pearson’s product moment correlation was calculated between the relative percentage of changes under each category and the score of the countries along the particular dimension of Hofstede. For this exploratory study, it is assumed that correlations with absolute values greater than 0.5 are sufficient to indicate the tendency of the relation between the category and the score in Hofstede’s dimensions. Table 3 shows the values of Hofstede’s dimensions for the four countries under investigation.
Table 3. Score of the countries in Hofstede’s dimensions (Hofstede, 1991)
| ||French page||German page||Japanese page||Dutch page|
|Power Distance Index (PDI)||68||35||54||38|
|Individualism Index (IDV)||71||67||46||80|
|Masculinity Index (MAS)||43||66||95||14|
|Uncertainty Avoidance Index (UAI)||86||65||92||53|
Table 4 shows the relevant correlations, along with their associated p values, found between the cultural dimension scores of each country and the number of contributions in some of the investigated categories. The categories with an absolute correlation coefficient less than 0.5 (Add Link, Format, Style/Typography, Reversion, and Vandalism) were not considered relevant and are excluded. Although many correlations are not significant (mostly due to the small number of countries investigated), the analysis identifies trends that are worth considering. In addition to the statistically significant correlations (p < 0.05), these trends will be used to support or reject our hypotheses.
Table 4. Summary of strong correlations
| ||Power Distance Index (PDI)||Individualism Index (IDV)||Masculinity Index (MAS)||Uncertainty Avoidance Index (UAI)|
|Add Information|| ||−0.98 (p = 0.008)||0.99 (p = 0.004)||0.72 (p = 0.141)|
|Clarify Information|| ||−0.69 (p = 0.155)||0.85 (p = 0.076)|| |
|Delete Information||−0.72 (p = 0.142)|| |
|Delete Link||−0.91 (p = 0.047)|| ||−0.64 (p = 0.178)|
|Fix Link|| ||0.84 (p = 0.082)||−0.72 (p = 0.139)|| |
|Grammar|| ||0.67 (p = 0.163)||−0.62 (p = 0.192)|| |
|Mark-up Language|| ||−0.52 (p = 0.242)|
|Spelling||0.64 (p = 0.180)||0.57 (p = 0.215)||−0.63 (p = 0.183)|| |