Cited by 381Ethics and Social Impacts of AISocial Media and PoliticsMisinformation and Its Impacts

Experiencing algorithms: How young people understand, feel about, and engage with algorithmic news selection on social media

Open access
Swart, Joëlle·2021·Social Media + Society

Abstract

The news that young people consume is increasingly subject to algorithmic curation. Yet, while numerous studies explore how algorithms exert power in citizens’ everyday life, little is known about how young people themselves perceive, learn about, and deal with news personalization. Considering the interactions between algorithms and users from an user-centric perspective, this article explores how young people make sense of, feel about, and engage with algorithmic news curation on social media and when such everyday experiences contribute to their algorithmic literacy. Employing in-depth interviews in combination with the walk-through method and think-aloud protocols with a diverse group of 22 young people aged 16–26 years, it addresses three current methodological challenges to studying algorithmic literacy: first, the lack of an established baseline about how algorithms operate; second, the opacity of algorithms within everyday media use; and third, limitations in technological vocabularies that hinder young people in articulating their algorithmic encounters. It finds that users’ sense-making strategies of algorithms are context-specific, triggered by expectancy violations and explicit personalization cues. However, young people’s intuitive and experience-based insights into news personalization do not automatically enable young people to verbalize these, nor does having knowledge about algorithms necessarily stimulate users to intervene in algorithmic decisions.

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Crossref · 10.1177/20563051211008828

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64 of 64 references verified0 citation errors · 0 not checkable

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  • Algorithms in search and social media limit user agency by making decisions about what information to display and filter out.

    “Despite their helpfulness in limiting information overload in the domains of search and social media, these algorithms also limit user agency by making decisions about what information to display and filter out (Swart, 2021).”

    From Expanding on the Frames: Making a Case for Algorithmic Literacy (2023) · cites this paper as Swart, 2021

  • A study found that although adolescents might understand that their actions influence the algorithm, thus determining the content they see, they often do not adjust their social media behaviors or clearly express their understanding of how algorithms work.

    “A study found that, although adolescents might understand that their actions influence the algorithm, thus determining the content they see, they often do not adjust their social media behaviors or clearly express their understanding of how algorithms work [37].”

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Authors
Swart, J.
Affiliations
University of Groningen (NL)
Corresponding author
Swart, Joëlle
Venue
Social Media + Society
Published
2021-04
Volume
7
Issue
2
ISSN
2056-3051 (ISSN-L)
OpenAlex
W3152734712
Cited by
381
References
65
Citations by year
2026: 83 · 2025: 99 · 2024: 89 · 2023: 67 · 2022: 37 · 2021: 6
FWCI
62.21
Type
journal article
Language
en
Open access
Locations
  • Social Media + Society (publishedVersion, cc-by)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, cc-by)
Funders
Faculty of Arts, University of Groningen (Writing up grant Faculty of Arts)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Communication › Social Media and Politics
  • Social Sciences › Sociology and Political Science › Misinformation and Its Impacts
Keywords
algorithmic literacy, personalized news, youth, social media, algorithmic opacity, expectancy violation, algorithmic intervention

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