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Should we worry about filter bubbles?

Author

Listed:
  • Zuiderveen Borgesius, Frederik J.
  • Trilling, Damian
  • Möller, Judith
  • Bodó, Balázs
  • de Vreese, Claes H.
  • Helberger, Natali

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.

Suggested Citation

  • Zuiderveen Borgesius, Frederik J. & Trilling, Damian & Möller, Judith & Bodó, Balázs & de Vreese, Claes H. & Helberger, Natali, 2016. "Should we worry about filter bubbles?," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 5(1), pages 1-16.
    • Handle: RePEc:zbw:iprjir:214006
    DOI: 10.14763/2016.1.401
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    References listed on IDEAS

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    Cited by:

    1. Theodora A. Maniou & Andreas Veglis, 2020. "Employing a Chatbot for News Dissemination during Crisis: Design, Implementation and Evaluation," Future Internet, MDPI, vol. 12(7), pages 1-14, June.
    2. Anna Gerbrandy, 2019. "Rethinking Competition Law within the European Economic Constitution," Journal of Common Market Studies, Wiley Blackwell, vol. 57(1), pages 127-142, January.
    3. Noskova, Victoriia, 2021. "Voice assistants as gatekeepers for consumption? How information intermediaries shape competition," Ilmenau Economics Discussion Papers 161, Ilmenau University of Technology, Institute of Economics.
    4. Copland, Simon, 2020. "Reddit quarantined: Can changing platform affordances reduce hateful material online?," Internet Policy Review: Journal on Internet Regulation, Alexander von Humboldt Institute for Internet and Society (HIIG), Berlin, vol. 9(4), pages 1-26.
    5. Iina Savolainen & Markus Kaakinen & Anu Sirola & Aki Koivula & Heli Hagfors & Izabela Zych & Hye-Jin Paek & Atte Oksanen, 2020. "Online Relationships and Social Media Interaction in Youth Problem Gambling: A Four-Country Study," IJERPH, MDPI, vol. 17(21), pages 1-18, November.
    6. Germano, Fabrizio & Sobbrio, Francesco, 2020. "Opinion dynamics via search engines (and other algorithmic gatekeepers)," Journal of Public Economics, Elsevier, vol. 187(C).
    7. Budzinski, Oliver & Gänßle, Sophia & Lindstädt-Dreusicke, Nadine, 2021. "Data (r)evolution - The economics of algorithmic search and recommender services," Ilmenau Economics Discussion Papers 148, Ilmenau University of Technology, Institute of Economics.
    8. Herzog, Bodo, 2019. "Optimal policy under uncertainty and rational inattention," Research in International Business and Finance, Elsevier, vol. 50(C), pages 444-449.
    9. Kim, Jungkeun & Kim, Jeong Hyun & Kim, Changju & Park, Jooyoung, 2023. "Decisions with ChatGPT: Reexamining choice overload in ChatGPT recommendations," Journal of Retailing and Consumer Services, Elsevier, vol. 75(C).
    10. Guohui Song & Yongbin Wang, 2021. "Mainstream Value Information Push Strategy on Chinese Aggregation News Platform: Evolution, Modelling and Analysis," Sustainability, MDPI, vol. 13(19), pages 1-17, October.
    11. Irion, Kristina & Helberger, Natali, 2017. "Smart TV and the online media sector: User privacy in view of changing market realities," Telecommunications Policy, Elsevier, vol. 41(3), pages 170-184.
    12. Annelien Smets & Jorre Vannieuwenhuyze & Pieter Ballon, 2022. "Serendipity in the city: User evaluations of urban recommender systems," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(1), pages 19-30, January.
    13. Thomas E. Powell & Toni G. L. A. van der Meer & Carlos Brenes Peralta, 2019. "Picture Power? The Contribution of Visuals and Text to Partisan Selective Exposure," Media and Communication, Cogitatio Press, vol. 7(3), pages 12-31.
    14. Chulmin Lim & Seongcheol Kim, 2024. "Examining factors influencing the user’s loyalty on algorithmic news recommendation service," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    15. Rui Qiao & Cong Liu & Jun Xu, 2024. "Making algorithmic app use a virtuous cycle: Influence of user gratification and fatigue on algorithmic app dependence," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-10, December.
    16. Pelletier, Mark J. & Horky, Alisha Blakeney & Fox, Alexa K., 2021. "Fexit: The effect of political and promotional communication from friends and family on Facebook exiting intentions," Journal of Business Research, Elsevier, vol. 122(C), pages 321-334.
    17. Sætra, Henrik Skaug, 2019. "The tyranny of perceived opinion: Freedom and information in the era of big data," Technology in Society, Elsevier, vol. 59(C).
    18. Thiel, Thorsten, 2017. "Digitalisierung als Kontext politischen Handelns. Republikanische Perspektiven auf die digitale Transformation der Gegenwart," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, pages 189-215.
    19. Kris Hartley & Minh Khuong Vu, 2020. "Fighting fake news in the COVID-19 era: policy insights from an equilibrium model," Policy Sciences, Springer;Society of Policy Sciences, vol. 53(4), pages 735-758, December.
    20. Kim, Jiwhan & Nam, Changi, 2019. "Analyzing continuance intention of recommendation algorithms," 30th European Regional ITS Conference, Helsinki 2019 205190, International Telecommunications Society (ITS).
    21. Sarah Eskens, 2020. "The personal information sphere: An integral approach to privacy and related information and communication rights," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(9), pages 1116-1128, September.
    22. Leyrer, Katharina, 2018. "Selektion und Bias in traditionellen und Internet-Informationsintermediären: Forschungsstand," Erlangen Contributions to Media Management and Media Economics 10/2018, Friedrich-Alexander University of Erlangen-Nuremberg (FAU), Institute for the Study of the Book, Professorship of E-Publishing and Digital Markets.
    23. König Pascal D., 2020. "Why Digital-Era Political Marketing is Not the Death Knell for Democracy: On the Importance of Placing Political Microtargeting in the Context of Party Competition," Statistics, Politics and Policy, De Gruyter, vol. 11(1), pages 87-110, June.
    24. Huw C Davies, 2018. "Redefining Filter Bubbles as (Escapable) Socio-Technical Recursion," Sociological Research Online, , vol. 23(3), pages 637-654, September.

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