Far-reaching effects of the filter bubble, the most notorious metaphor in media studies | SpringerLink
Published by Reblogs - Credits in Posts,
- Open Forum
- Published: 25 February 2022
Far-reaching effects of the filter bubble, the most notorious metaphor in media studies
AI & SOCIETY (2022)Cite this article
-
73 Accesses
Abstract
This article discusses the topic of algorithmic personalization and the creation of the so-called "filter bubble" effect, which is often understood as one of the most problematic influences of artificial intelligence on democratic social order. The author suggests that focusing on the issue of information diversity, which had far-reaching effect on the empirical research that tried to quantitatively measure and systematically prove the existence of the filter bubbles, was the wrong starting point for the discussion on the application of algorithmic personalization. It has drawn our attention away from the deeper issue: habit. Habitual adaptation of algorithmic personalization, namely, stands in essential contradiction to the ideal image of a non-adaptive public sphere, upon which democratic societies should be based. Focusing on habitual adaptation could also explain why users addictively stick to certain kinds of information, even if they are not caught in an isolated chamber.
This is a preview of subscription content, access via your institution.
Access options
Buy single article
Instant access to the full article PDF.
USD 39.95
Price includes VAT (USA)
Tax calculation will be finalised during checkout.
References
Bodó B, Helberger N, Eskens S, Möller J (2019) Interested in diversity. Digit Journal 7(2):206–229
Bozdag E (2013) Bias in algorithmic filtering and personalization. Ethics Inf Technol 15:209–227
Bastian M, Makhortykh M, Dobber T (2019) News personalization for peace: how algorithmic recommendations can impact conflict coverage. Int J Confl Manag 30(3):309–328
Chun WHK (2016) Updating to remain the same: habitual new media. The MIT Press, Cambridge
Haim M, Graefe A, Brosius H (2017) Burst of the filter bubble? Digit J 6(3):330–343
Kant T (2020) Making it personal: algorithmic personalization, identity, and everyday life. Oxford University Press, New York
LaRose R (2010) The problem of media habits. Commun Theory 20(2):194–222
Nechushtai E, Lewis SC (2019) What kind of news gatekeepers do we want machines to be? Filter bubbles, fragmentation, and the normative dimensions of algorithmic recommendations. Comput Hum Behav 90:298–307
Papacharissi Z, Streeter T, Gillespie T (2013) Culture digitally: habitus of the new. J Broadcast Electron Media 57(4):596–607
Pariser E (2011) The filter bubble: what the internet is hiding from you. Penguin Random House, New York
Roth C, Mazières A, Menezes T (2020) Tubes and bubbles topological confinement of YouTube recommendations. PLoS One 15(4):e0231703
Seaver N (2019) Captivating algorithms: recommender systems as traps. J Mater Cult 24(4):421–436
Splichal S (2019) Upodatkovljenje javnega mnenja: od normativne utopije do algoritemske distopije. Javnost - the Public 26(S1):1–22
Trielli D, Diakopoulos N (2020) Partisan search behavior and Google results in the 2018 U.S. midterm elections. Inf Commun Soc. https://doi.org/10.1080/1369118X.2020.1764605
Author information
Affiliations
Social Communication Research Centre, Faculty of Social Sciences, University of Ljubljana, Ljubljana, Slovenia
Jernej Kaluža
Corresponding author
Correspondence to Jernej Kaluža.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
AIS Volume: Special issue: Embedding AI in Society (EAIS)—volume to be allocated later.
Rights and permissions
About this article
Cite this article
Kaluža, J. Far-reaching effects of the filter bubble, the most notorious metaphor in media studies. AI & Soc (2022). https://doi.org/10.1007/s00146-022-01399-x
Received27 May 2021
Accepted07 February 2022
Published25 February 2022
DOIhttps://doi.org/10.1007/s00146-022-01399-x
Keywords
- Filter bubbles
- Algorithmic personalization
- Diversity
- Habit
- Public sphere
Over 10 million scientific documents at your fingertips
- Home
- Impressum
- Legal information
- Privacy statement
- California Privacy Statement
- How we use cookies
- Manage cookies/Do not sell my data
- Accessibility
- FAQ
- Contact us
- Affiliate program
Not logged in - 72.83.177.36
Not affiliated
© 2022 Springer Nature Switzerland AG. Part of Springer Nature.