4.1 INTRODUCTION
In study 3 (presented in chapter 2) we compared the behaviour of L1 users and L2 users. The server-centric approach restricted the investigation to those users who accessed the website. This raises the question of the degree to which the access of the website was determined by language:
either because only non-native speakers above a certain language proficiency level visited the website or because language determined how the website was linked to others. In order to answer
th is
In our theoretical discussion it was stated that non-native language navigation leads to a higher
cognitiv study
3 (see section 2.3.4.3.2). Study 8 aims to add information linking cognitive burden to user
principles on the entire Web. Suspicion that language and culture possibly bias link setting and link e question, the role of language as a potential barrier to access is examined in study 8 in th chapter.
e burden (see section 1.2.2.1.1). This statement was partly confirmed by results from satisfaction. Since the acceptance of a language is also expected to depend on the language offer of other providers (see section 1.2.2.2.1), satisfaction is also linked to the perceived amount of native language information online in the same study, i.e. to the perceived amount of native language alternatives.
The World Wide Web is a network with websites as nodes and hyperlinks representing the edges between the nodes. Websites are therefore mutually dependent entities that constitute a web-system (Park and Thelwall, 2003). This is particularly true with respect to their informational value. The structure of the WWW, or the way websites are linked to each other, determines the information flow and knowledge generation to a large extent.
As a network, the Internet can be investigated from a technical perspective as well as a social perspective. An example of technical investigation is the calculation of characteristic metrics such as the centrality or connectivity of a website. Algorithms that are based on these metrics are used, for example, to rank pages for displaying search results.
These algorithms are based on the assumption that the distribution of hyperlinks represents similar
differences in hyperlink distribution.
are set to link webpages.
However, we also consider it useful to examine the “flow of Internet users” within this framework, a
with differences in domain knowledge and language related cognitive effort.
oportion was 50% higher than the corresponding proportion using behaviour is raised. In fact, initial studies indicate the impact of culture: for example, Baeza-Yates and Poblete (2003) found national
Information flow can be described in terms of its intensity as well as with respect to its direction.
Culture and language are expected to affect both the number of links established between websites as well as which combination of websites are linked to each other. The term information flow is usually used in the context of hyperlink distribution, i.e. how hyperlinks
by an lysing their navigation patterns through a website.
Results from chapter 2 suggested that a higher percentage of physicians within the L2 user group accessed the website than within the L1 group. The divergence was explained
Another outcome of the two studies in chapter 2 is the fact that – independent of domain knowledge - the ratio of L1 users accessing the website considerably exceeds that of L2 users.
Among the 277,809 sessions examined in the logfile-based study, we were able to identify 236,507 sessions (= 83.2 %) as sessions of users who are native speakers of one of the languages offered on the website at that time (L1 users). 41,297 sessions (16.8 %) were L2 (non-native speakers) user sessions. There were thus significantly more L1 users than L2 users accessing the websites (p <
0.001 in a χ2-test). In addition, this pr
among all Internet users. In 2001, the proportion of native speakers of the site’s four languages among all Internet users was 55.9% (www.glreach.com).
Among the 135 valid answer sets of the questionnaire-based study, 113 (= 83.7%) were answers from L1 users, and 22 (=16.3%) from L2 users (p < 0.001 in a χ2-test). The ratio between native speakers and non-native speakers was therefore almost identical in both studies: significantly more L1 users than L2 users accessed the website. It should be noted that during the data collection of the follow-up study, French was offered as an additional language, which should have led to a higher percentage of native speakers compared to the first study. In 2004, the proportion of native speakers of the site’s five languages among all Internet users was 58.4% (www.glreach.com).
83,2% 83,7%
percentages of L1 users on the Internet*
16,8% users from logfile analyses and survey participants
* The lower line represents the languages that were “L1 languages” (English, German, Spanish, Portuguese) in the logfile analysis, data from 2001; the higher line represent the languages that were “L1 languages” (idem + French) in the
survey, data from 2004
Figure 19. Proportion of L1 and L2 Users who Accessed the Website/Participated in the Survey
These findings seem to clearly reveal the impact of users’ language-based cognitive effort on website access. Yet a limitation to such conclusion is the lack of control for a potential bias of the
impact on user satisfaction?
distribution between websites. Beyond this technical data, this chapter also returns to the question of how language affects the extent to which existing hyperlinks between websites are used. Finally, hyperlink distribution. In fact, for a more precise evaluation of the impact of language, insight into the number of links leading to the website is required. In contrast to culture, language is a much more visible and tangible characteristic of websites, in particular if websites are judged from a first glance. Our analysis of information flow focuses on language as a determinant of information flow.
The wide-spread use of L2 information presentation also gives rise to a number of further questions: Does the users’ perception of the amount of information offered in their native languages affect their attitude towards L2 language websites? Do their proficiency levels have an
This chapter investigates the extent to which language represents a barrier to the flow of information on the Internet. We examine whether mechanisms of demand and supply determine the number of webhosts per language, and to which extent these affect language-related link
h a website.
populations, diminishing the digital divide.
hyperlink networks are predominantly based on distances and the connectivity between websites and derived measures, such as centrality or cluster analyses (Adamic
ce supporting the impact of the social environment on hyperlinks was also found. Knowledge about its impact is important when information about quality is derived, e.g. from an analysis of how many links are set and to which websites (Park, 2003).
Authors focussing on social processes analysed these in terms of both the source and the result of hyperlink setting behaviour. The term social processes embraces a number of different phenomena.
Data is obtained from metrics concerning the degree of linkage between websites and interpreted with regard to social and communicational ties. McPherson and his colleagues have, for example, argued that Confucianism is a major reason for homogeneity among South Korean political groups we investigate whether or not language-related mechanisms of demand and supply also affect users’
attitudes and satisfaction wit
Insight from this chapter provides further knowledge about the importance of a website’s language(s) when attracting users. This type of information is useful for commercial websites but also for websites with the goal of social benefice. It also provides help with promoting health information among large user
4.2 LITERATURE REVIEW: THE ROLE OF LANGUAGE (AND CULTURE)
WITH REGARD TO HYPERLINK SETTING AND FOLLOWING BEHAVIOUR