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Responsibility networks in media discourses on automation: A comparative analysis of social media algorithms and social companions
University of Zurich, Switzerland.ORCID iD: 0000-0001-8018-6439
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Department of Geography, Media and Communication (from 2013).ORCID iD: 0000-0002-8504-5691
University of Vienna, Austria.
2023 (English)In: New Media and Society, ISSN 1461-4448, E-ISSN 1461-7315Article in journal (Refereed) Epub ahead of print
Abstract [en]

The diffusion of algorithms, robots, and artificial intelligence has sparked public debates regarding opportunities, risks, and responsibility for addressing problems and developing solutions. Since media cover and shape sociotechnical imaginaries, this study investigates the Austrian media discourses on responsibility in two domains of automation: social media algorithms and social companions. Using a machine learning approach, relevant articles were identified, followed by a manual comparative content analysis. The findings indicate that media coverage of social media algorithms tends to be more critical compared to social companions. In the debate about social media algorithms, journalists emerge as the most common speakers raising responsibility issues and primarily attributing them to Internet platform providers. Conversely, responsibility for social robotics is predominantly articulated by experts, considering it as a responsibility shared by society, economy, and research. Furthermore, the media present different perspectives on the agency and responsibility of social media algorithms and social robots themselves.

Place, publisher, year, edition, pages
Sage Publications, 2023.
Keywords [en]
Algorithms, automation, content analysis, media coverage, responsibility networks, social companions, social media
National Category
Media Studies
Research subject
Media and Communication Studies
Identifiers
URN: urn:nbn:se:kau:diva-97193DOI: 10.1177/14614448231203310ISI: 001090261900001Scopus ID: 2-s2.0-85174508153OAI: oai:DiVA.org:kau-97193DiVA, id: diva2:1807631
Available from: 2023-10-27 Created: 2023-10-27 Last updated: 2023-11-27Bibliographically approved

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Brantner, Cornelia

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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Language
  • de-DE
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Output format
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