This paper aims to further explore the drivers of citizens' decisions about social and political participation on the Internet, as mixed empirical evidence has been found in the literature. Such extension efforts have mainly focused on individual resources and in particular on the inclusion of variables related to digital skills, while little is known about the role of group resources and institutional context. Such elements determine the individual's position within his social and economic relations.
As for citizens' opinions on the Internet's potential for political participation, some recent figures are shown in the last two reports of the World Internet Project (March and December respectively; Cole, Suman, Schramm, Lunn, Zhou, Tang and Ognyanova, 2012a;Cole, Suman, Schramm, Zhou, &. Along the same lines, the role of online social networks as group resources for social and political participation on the Internet remains little explored in the resource approach, in contrast to the emerging literature examining the effects of social media on study the political participation of citizens. In particular, the information collected is summarized in the so-called E-Participation Index (United Nations, 2012).
Individuals classified as Internet users were, for the first time in the history of this survey11, asked about their engagement in social and political participation on the Internet. Data shows that 67.1% of people between the ages of 16 and 74 have used the Internet in the last three months. The Nordic countries have the highest rates in both types of online activities: in the first type of participation, the leading countries are Finland and Norway, where respectively 43% and 40% of their population read or give an opinion on social and political issues on the Internet.
Social and political participation online in the European Union, Iceland and Norway (percentages of individuals aged 16 to 74).
Econometric model
Separate probit regressions (controlling for selection bias, respectively) have been run for each of these variables to assess whether there are differences in the factors influencing them. First, demographic characteristics of individuals are taken into account: income13, level of education, employment status, gender, age14 and city size. As mentioned in Section 4.1, the literature indicates that the estimation of a probit model that controls for selection bias requires excluding at least one of the variables considered in the selection equation (Greene, 2007).
In particular, an index of digital skills is developed by calculating the average number of tasks performed by an individual and then normalizing this to a scale of 0-1. 14 The estimates also include the square of age to account for the fact that the relationship between age and participation may not be linear. Third, political interest is measured using a dummy variable that takes into account whether an individual usually reads news online.
In the present analysis, it is assumed that reading news online at least to some extent indicates an individual's interest in current socio-economic conditions and politics. In particular, we use a composite index, which is the regional version of the one developed to benchmark the accessibility of e-government within the framework of the European plan i201016 (Capgemini, Sogeti, IDC, RAND Europe & Teknologisk Institut, 2010 ; Eurostat, 2011).
Concluding remarks
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