The DOI matches its Crossref record; 64 of the 65 references it cites were found in a registry or an index.
Experiencing Algorithms: How Young People Understand, Feel About, and Engage With Algorithmic News Selection on Social Media
Open accessAbstract
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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“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
In the citing paper
“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].”
From Social Media Use in Adolescents: Bans, Benefits, and Emotion Regulation Behaviors (2024) · cites this paper as [37]
Citations
Cites
Basics of Qualitative Research: Techniques and Procedures for Developing Grounded Theory
Wuetherick, B. (2010) · Canadian Journal of University Continuing Education · doi:10.21225/d5g01t · Cited by 8,333
The Black Box Society: The Secret Algorithms That Control Money and Information
Pasquale, F. (2015) · doi:10.4159/harvard.9780674736061 · Cited by 3,796
Space and Place: The Perspective of Experience
Patricios, N. N., & Tuan, Y. (1979) · Leonardo · doi:10.2307/1574234 · Cited by 3,570
How the machine “thinks”: Understanding opacity in machine learning algorithms
Burrell, J. (2016) · Big Data & Society · doi:10.1177/2053951715622512 · Cited by 3,196 · cited 2×
“This makes their logics difficult to entangle, even for highly skilled engineers (Burrell, 2016; Seaver, 2017).”
Backgroundvan Dijck, J., Poell, T., & de Waal, M. (2018) · doi:10.1093/oso/9780190889760.001.0001 · Cited by 2,951
Thinking critically about and researching algorithms
Kitchin, R. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1154087 · Cited by 1,471
The algorithmic imaginary: exploring the ordinary affects of Facebook algorithms
Bucher, T. (2016) · Information Communication & Society · doi:10.1080/1369118x.2016.1154086 · Cited by 1,420
If...Then: Algorithmic Power and Politics
Bucher, T. (2018) · doi:10.1093/oso/9780190493028.001.0001 · Cited by 1,223
The walkthrough method: An approach to the study of apps
Light, B., Burgess, J., & Duguay, S. (2016) · New Media & Society · doi:10.1177/1461444816675438 · Cited by 1,165
Playing the visibility game: How digital influencers and algorithms negotiate influence on Instagram
Cotter, K. (2019) · New Media & Society · doi:10.1177/1461444818815684 · Cited by 1,025
Research works printed but not linked: 4
- Cotter K., 2020, International Journal of Communication, 14, 745
- D’Ignazio C., 2015, Proceedings of the Bloomberg Data for Good Exchange Conference
- Klawitter E., 2018, International Journal of Communication, 12, 3490
- Schmidt J., 2019, International Journal of Communication, 13, 853
Cited by
Sorted by citations
Kang, H., & Lou, C. (2022) · Journal of Computer-Mediated Communication · doi:10.1093/jcmc/zmac014 · Cited by 353
Shin, D., Kee, K. F., & Shin, E. Y. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102494 · Cited by 201
Advancing a Radical Audience Turn in Journalism. Fundamental Dilemmas for Journalism Studies
Swart, J., Kormelink, T. G., Meijer, I. C., & Broersma, M. (2022) · Digital Journalism · doi:10.1080/21670811.2021.2024764 · Cited by 158
Self-citationEg, R., Tønnesen, O. D., & Tennfjord, M. K. (2022) · Computers in Human Behavior Reports · doi:10.1016/j.chbr.2022.100253 · Cited by 137
Learning to like TikTok . . . and not: Algorithm awareness as process
Siles, I., Valerio-Alfaro, L., & Moran, A. M. (2022) · New Media & Society · doi:10.1177/14614448221138973 · Cited by 142
Metadata
- Authors
- Swart, J.
- Affiliations
- University of Groningen (NL)
- Corresponding author
- Swart, Joëlle
- ORCID
- Swart, Joëlle
- Venue
- Social Media + Society
- Publisher
- SAGE Publications
- 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
- gold
- doi.org
- 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
- Physical Sciences › Computer Science › Artificial Intelligence › 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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