Algorithm dependency in platformized news use

dc.contributor.authorSchaetz, Nadja
dc.contributor.authorGagrčin, Emilija
dc.contributor.authorToth, Roland
dc.contributor.authorEmmer, Martin
dc.date.accessioned2023-09-19T15:43:25Z
dc.date.available2023-09-19T15:43:25Z
dc.date.issued2023
dc.description.abstractPrevious research has highlighted the ambiguous experience of algorithmic news curation whereby people are simultaneously comfortable with algorithms, but also concerned about the underlying data collection practices. The present article builds on media dependency theory and news-finds-me (NFM) perceptions to explore this tension. Empirically, we analyze original survey data from six European countries (Germany, Sweden, France, Greece, Poland, and Italy, n = 2,899) to investigate how young Europeans’ privacy concerns and attitudes toward algorithms affect NFM. We find that a more positive attitude toward algorithms and more privacy concerns are related to stronger NFM. The study highlights power asymmetries in platformized news use and suggests that the ambivalent experiences might be a result of algorithm dependency, whereby individuals rely on algorithms in platformized news use to meet their information needs, despite accompanying risks and concerns.
dc.identifier.citationSchaetz, N., Gagrčin, E., Toth, R., & Emmer, M. (2023). Algorithm dependency in platformized news use. New Media & Society. https://doi.org/10.1177/14614448231193093
dc.identifier.doi10.1177/14614448231193093
dc.identifier.issn1461-4448, 1461-7315
dc.identifier.urihttps://www.weizenbaum-library.de/handle/id/369
dc.language.isoeng
dc.rightsopen access
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleAlgorithm dependency in platformized news use
dc.typeArticle
dc.type.statuspublishedVersion
dcmi.typeText
dcterms.bibliographicCitation.booktitleNew Media & Society
dcterms.bibliographicCitation.doi10.1177/14614448231193093
dcterms.bibliographicCitation.pagestart14614448231193093
dcterms.bibliographicCitation.urlhttp://journals.sagepub.com/doi/10.1177/14614448231193093
local.researchgroupMethodenlab
local.researchgroupWeizenbaum Panel
local.researchtopicWeizenbaum Digital Science Center
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