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An Empirical Study Concerning Filter Bubbles and Echo Chambers: The perception of personalized content in news applications.
Södertörn University, School of Natural Sciences, Technology and Environmental Studies, Media Technology.
Södertörn University, School of Natural Sciences, Technology and Environmental Studies, Media Technology.
2018 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The aim of this study was to investigate the perception of personalization on news applications and to examine to what extent it is seen as an optimal solution for users to receive information. Due to the growth of online news and digital journalism the amount of information that is being published online is significantly higher nowadays than it has previously been. Therefore, a recommendation system called personalization has been introduced to choose content for the reader. Many concerns of personalization have already been brought to light, these concerns are believed to be contributing to filter bubbles and echo chambers. This study will investigate these concerns further in order to understand the users. The methodology used in the study were semi-structured interviews and an analysis based on the concerns brought forward by Borgesius et al. Six interviews were conducted with users and two were conducted with major news organizations in Sweden. The results of the study indicate that users fear personalization will cause filter bubbles and polarization due to them only being subjected to one perspective. The users are unaware as to how personalization works and therefore question why it is being introduced into news applications. Due to personalization being a new phenomenon news applications it is not yet seen as an optimal solution by users or news organizations. There are, however, many factors that can assist in its development such as transparency and awareness of the phenomenon.

Place, publisher, year, edition, pages
2018. , p. 73
Keywords [en]
Personalization, echo chambers, filter bubbles, news applications, online news, digital journalism
National Category
Media Engineering
Identifiers
URN: urn:nbn:se:sh:diva-39124OAI: oai:DiVA.org:sh-39124DiVA, id: diva2:1358040
Subject / course
Media Technology
Uppsok
Technology
Supervisors
Available from: 2019-10-07 Created: 2019-10-06 Last updated: 2019-10-07Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • harvard-anglia-ruskin-university
  • apa-old-doi-prefix.csl
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf