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Filter Bubble Effects on Deliberative Democracy? – A Realist Synthesis of Empirical Research

Wisbrant, Jonas LU (2016) SKPM08 20161
Department of Strategic Communication
Abstract
In 2011 Eli Pariser coined the term ‘filter bubble’ and warned that online algorithm driven filters based on users’ click behaviour, would risk to reduce the diversity of public discourses and thereby deliberative democracy. Through the multidisciplinary and iterative Realist Synthesis method, the aim of the study has been to synthesise empirically based understanding of how online algorithm driven filter bubbles affect public discourses and deliberative democracies.

On micro level, the result confirms selection bias and corresponding confirmation bias in the contexts of online feed oriented political messages that would constitute a necessary key condition for algorithm driven filter bubbles to emerge. However, none of the studies in... (More)
In 2011 Eli Pariser coined the term ‘filter bubble’ and warned that online algorithm driven filters based on users’ click behaviour, would risk to reduce the diversity of public discourses and thereby deliberative democracy. Through the multidisciplinary and iterative Realist Synthesis method, the aim of the study has been to synthesise empirically based understanding of how online algorithm driven filter bubbles affect public discourses and deliberative democracies.

On micro level, the result confirms selection bias and corresponding confirmation bias in the contexts of online feed oriented political messages that would constitute a necessary key condition for algorithm driven filter bubbles to emerge. However, none of the studies in the sample have explicitly investigated effects of these filters on political attitudes. Therefore, filter bubble effects on public discourses and democracy can neither be verified, measured nor refuted.

On the meso level, the presence of online clusters of biased online political content, that could serve as foundations for online echo chambers, are shown, and their inner workings partly explained. Also shown is that these environments have the potential to reduce the diversity of political discourses, but also to support polarisation and radicalisation.
On macro level the results indicate that national borders, power distribution of political websites, and personalisation through localisation, language and political topics, differentiate what Internet users see when surfing or searching the web in a way that could affect diversity of global or national political discourses.

The results also indicate stratification of discourses where some users with high topic involvement, curiosity or interest in politics are relatively immune to political selection bias, while other groups of less interested or knowledgeable followers, are likely to be reached by less diversified messages.

Limited to the sampled research, this meta study shows that contemporary Internet brings challenges to deliberative democracy, but until further not because of algorithm driven filter bubbles. (Less)
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author
Wisbrant, Jonas LU
supervisor
organization
course
SKPM08 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8893243
date added to LUP
2018-01-10 09:08:32
date last changed
2018-01-10 09:08:32
@misc{8893243,
  abstract     = {In 2011 Eli Pariser coined the term ‘filter bubble’ and warned that online algorithm driven filters based on users’ click behaviour, would risk to reduce the diversity of public discourses and thereby deliberative democracy. Through the multidisciplinary and iterative Realist Synthesis method, the aim of the study has been to synthesise empirically based understanding of how online algorithm driven filter bubbles affect public discourses and deliberative democracies. 

On micro level, the result confirms selection bias and corresponding confirmation bias in the contexts of online feed oriented political messages that would constitute a necessary key condition for algorithm driven filter bubbles to emerge. However, none of the studies in the sample have explicitly investigated effects of these filters on political attitudes. Therefore, filter bubble effects on public discourses and democracy can neither be verified, measured nor refuted. 

On the meso level, the presence of online clusters of biased online political content, that could serve as foundations for online echo chambers, are shown, and their inner workings partly explained. Also shown is that these environments have the potential to reduce the diversity of political discourses, but also to support polarisation and radicalisation. 
On macro level the results indicate that national borders, power distribution of political websites, and personalisation through localisation, language and political topics, differentiate what Internet users see when surfing or searching the web in a way that could affect diversity of global or national political discourses. 

The results also indicate stratification of discourses where some users with high topic involvement, curiosity or interest in politics are relatively immune to political selection bias, while other groups of less interested or knowledgeable followers, are likely to be reached by less diversified messages. 

Limited to the sampled research, this meta study shows that contemporary Internet brings challenges to deliberative democracy, but until further not because of algorithm driven filter bubbles.},
  author       = {Wisbrant, Jonas},
  language     = {eng},
  note         = {Student Paper},
  title        = {Filter Bubble Effects on Deliberative Democracy? – A Realist Synthesis of Empirical Research},
  year         = {2016},
}