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Challenges of Digital Politics at the Subnational Level in Sweden: Descriptions and Explanations of Social Media Usage

  • Gustav LidénEmail author
Chapter
Part of the Public Administration and Information Technology book series (PAIT, volume 29)

Abstract

Since a number of years the use of social media in political processes appears to have had a significant effect on the political landscape. Irrespective of advantages or disadvantages of such technologies scholars have revealed great differences in how digital technologies have been adopted among subnational entities. Citizens risk facing substantial varieties in preconditions for the utilization of digitally based tools based on their residency. In this book chapter on Swedish municipalities adoption of social media both descriptions and patterns explaining variation in such adoption are studied. Findings indicate that an overwhelming majority of Swedish municipalities use social media. Based on the time period applied it can also be noticed that this proportion has increased annually. The explanatory models reveal particularly two noteworthy findings. First, larger municipalities with an already well-developed website are more inclined to adopt social media. As an additional predictor, municipalities with certain funding for democratic development shows a similar pattern. Second, when assessing municipalities versatility in social media usage two of the these predictors show relevance. Lager municipalities with an advanced website are more inclined to utilize social media for different reasons. Since this book chapter shows that certain resources, such as an already developed website and a larger population, will pose influence on social media usage the distribution of this form of digital technology can be distributed unequal over societies.

Keywords

Social Media Users Digital Politics Swedish Municipalities Municipal Users Municipal Websites 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Social SciencesMid SwedenUniversitySundsvallSweden

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