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Cited by 541Media Influence and PoliticsSocial Media and PoliticsMisinformation and Its Impacts

Should we worry about filter bubbles?

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Zuiderveen Borgesius, Frederik J., Trilling, Damian, Möller, Judith, Bodó, Balázs, de Vreese, Claes H., Helberger, Natali·2016·Internet Policy Review
DOI 10.14763/2016.1.401
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Abstract

Some fear that personalised communication can lead to information cocoons or filter bubbles.For instance, a personalised news website could give more prominence to conservative or liberal media items, based on the (assumed) political interests of the user.As a result, users may encounter only a limited range of political ideas.We synthesise empirical research on the extent and effects of self-selected personalisation, where people actively choose which content they receive, and pre-selected personalisation, where algorithms personalise content for users without any deliberate user choice.We conclude that at present there is little empirical evidence that warrants any worries about filter bubbles.

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  • The empirical evidence does not support the existence of echo chambers and filter bubbles as actual, observable phenomena in public communication; there is a pronounced absence of evidence that genuine filter bubbles or echo chambers are real, outside of highly specific and unusual contexts.

    “While the empirical evidence does not support the existence of echo chambers and filter bubbles as actual, observable phenomena in public communication”

    From Filter bubble (2019) · cites this paper as Zuiderveen Borgesius et al., 2016

    The 6. CONCLUSION says there is no empirical evidence warranting strong worries about filter bubbles, and the section on prevalence of self-selected personalisation says that, if echo chambers exist, their walls are porous. That supports skepticism about their prevalence or effects, but not the stronger claim that empirical evidence does not support their existence as observable phenomena in public communication. The paper does not confine their existence to highly specific or unusual contexts. (LLM, conf=0.87)

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Research works printed but not linked: 14

  1. Beam, M. A., & Kosicki, G. M. (2014). Personalized news portals: Filtering systems and increased news exposure. Journalism & Mass Communication Quarterly, 91(1), 59-77.
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  6. Morgan, J. S., Shafiq, M. Z., & Lampe, C. (2013). Is news sharing on Twitter ideologically biased ? In Proceedings of the 2013 conference on Computer supported cooperative work (pp. 887-897). ACM.
  7. O'Callaghan, D., Greene, D., Conway, M., Carthy, J., & Cunningham, P. (2013). The extreme right filter bubble. arXiv preprint arXiv:1308.6149. · arXiv
  8. Price, V., Cappella, J. N., & Nir, L. (2002). Does disagreement contribute to more deliberative opinion? Political Communication, 19(1), 95-112.
  9. Sears, D. O., & Freedman, J. L. (1967). Selective exposure to information: A critical review. Public Opinion Quarterly, 31(2), 194-213.
  10. Sunstein, C. R. (2002). Republic.com. Princeton, NJ: Princeton University Press.
  11. Trilling, D., & Schoenbach, K. (2013a). Patterns of news consumption in Austria: How fragmented are they? International Journal of Communication, 7, 929-953.
  12. Trilling, D., & Schoenbach, K. (2015). Investigating people's news diets: How online news users use offline news. Communications: The European Journal of Communication Research, 40(1), 67-91.
  13. Wojcieszak, M. E., & Mutz, D. C. (2009). Online groups and political discourse: Do online discussion spaces facilitate exposure to political disagreement? Journal of Communication, 59(1), 40-56.
  14. Wijfjes, H. (ed.) (2004). Journalistiek in Nederland. Beroep, cultuur en organisatie 1850-2000. Amsterdam, Netherlands: Boom.

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Authors
Zuiderveen Borgesius, F. J., Trilling, D., Möller, J., Bodó, B., de Vreese, C. H., & Helberger, N.
Affiliations
University of Amsterdam (NL)
ORCID
Venue
Internet Policy Review
Publisher
Internet Policy Review, Alexander von Humboldt Institute for Internet and Society
Published
2016-03-31
Volume
5
Issue
1
ISSN
2197-6775 (ISSN-L)
DOI
10.14763/2016.1.401
OpenAlex
W2340526123
Cited by
541
References
49
Citations by year
2026: 31 · 2025: 42 · 2024: 46 · 2023: 60 · 2022: 64 · 2021: 78 · 2020: 95 · 2019: 67 · 2018: 40 · 2017: 18
FWCI
119.14
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Internet Policy Review (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • UvA-DARE (University of Amsterdam) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Econstor (Econstor) (submittedVersion, cc-by)
  • Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Topics
  • Social Sciences › Sociology and Political Science › Media Influence and Politics
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
Keywords
filter bubbles, information cocoons, algorithmic personalization, political polarization, news media, user choice

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