INFORMATION SOCIETY FOR ALL? STRUCTURAL CHARACTERISTICS OF INTERNET USE IN 15 EUROPEAN COUNTRIES

ABSTRACT

The article examines the patterns of Internet use in 15 European Union countries. In the theoretical part, it is discussed how the social scientists have addressed the consequences of the diffusion of the new information and communication technologies (ICT). It is asked whether there is a potential in the use of ICT for increasing social inequalities within and between the affluent societies. In the empirical part, it is examined whether the 15 European countries selected have qualitatively different patterns of Internet use from each other. Results from Eurobarometer 56.0 survey data collected in 2001 (N=16,200) show that the basic socio-demographic factors explain the use of the Internet rather similarly in the then EU area. However, it is also revealed that the institutional differences between European countries affect the strengths of socio-demographic factors.

Keywords:

• Internet
• digital divide
• socio-demographic factors
• institutional differences
• welfare regimes

I would like to thank Anu Raijas, Juho Härkönen and my colleagues at the Turku Center for Welfare Research, and European Societies reviewers for useful comments.

Notes

¹The variable ‘European weight 15’ is considered to be the best weight if the EU population is analysed as whole (see http://www.gesis.org/en/data_service/eurobarometer/standard_eb/ebweight.htm). This variable is applied when the data are weighted.

²The question was originally evaluated using a seven-point scale, in which 1 = ‘every day’, 2 = ‘several times a week’, 3 = ‘once a week’, 4 = ‘one to three times a month’, 5 = ‘less often’, 6 = ‘never’, 7 = ‘don't know’. The variable was dichotomised for subsequent analyses by applying options three and four as cut-off values. In addition, answers with the seventh option (N=102) were excluded.

³The weight coefficient available in the data is calculated to show how many individuals out of the total EU population are represented by a particular case. If the original weight is divided by the sample only a few cases will be left for the small countries (see Table 1).

⁴The odds ratio is the increase (or decrease if the ratio is less than one) in the odds of being in one outcome category when the value of the independent increases by one unit.

⁵About 10 to 25 per cent of the predicted outcomes within regimes are based on only one value observed in the dependent variable. The high proportion of these outcomes results from the fact that age and education are included in the same model. For this reason, interpretations concerning patterns of Internet use frequency will be made on the basis of the main-effect tests only.