Who dominates the discourse on text-generative artificial intelligence? The presence of performative, epistemic and evaluating experts in German newspaper coverage of an emerging technology

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Cover of Volume: SCM Studies in Communication and Media Volume 15 (2026), Issue 2
Open Access Full access

SCM Studies in Communication and Media

Volume 15 (2026), Issue 2

Authors:
Publisher
Nomos, Baden-Baden
Copyright Year
2026
ISSN-Online
2192-4007
ISSN-Print
2192-4007

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Open Access Full access

Volume 15 (2026), Issue 2

Who dominates the discourse on text-generative artificial intelligence? The presence of performative, epistemic and evaluating experts in German newspaper coverage of an emerging technology

Authors:
ISSN-Print
2192-4007
ISSN-Online
2192-4007
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The public AI discourse is shaped by visions and interpretations that influence how this emerging technology is perceived, assessed, developed and applied in society. Generating acceptance for a particular vision has thus become a central objective for various societal actors engaging with the new technology. Recently, (tech) entrepreneurs appear to have been more successful than others in advancing their visions of AI. Assuming a powerful journalism in selecting actors and presenting their statements to the public, several scholars attribute this disproportionate influence to an economically biased media coverage of AI. We propose a conceptual framework that distinguishes actors according to their AI-related expertise and apply it in a semi-automated content analysis of the media coverage of text-generative AI tools such as ChatGPT in German print media. Within the articles published between November 2022 and April 2024 in ten newspapers, scientists and entrepreneurs were the most frequently represented groups. Business-related practical expertise regarding AI development dominated the debate compared to science-related epistemic knowledge about the technology’s functionality or its professional impact assessment. Our findings nuance the presumed dominance of economic actors in the mediated AI discourse by revealing a nearly balanced appearance of scientists and entrepreneurs. The results point to a shortage of independent evaluations of the technology’s functionality in the form of epistemic expertise.

Bibliography

  1. Acemoglu, D., & Johnson, S. (2023). Power and progress: Our thousand-year struggle over technology and prosperity. Basic Books. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  2. Akbik, A., Blythe, D., & Vollgraf, R. (2018). Contextual string embeddings for sequence labeling. 27th International Conference on Computational Linguistics, 1638–1649. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  3. Albæk, E., Christiansen, P. M., & Togeby, L. (2003). Experts in the mass media: Researchers as sources in Danish daily newspapers, 1961–2001. Journalism & Mass Communication Quarterly, 80(4), 937–948. https://doi.org/10.1177/107769900308000412 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  4. Albæk, E. (2011). The interaction between experts and journalists in news journalism. Journalism, 12(3), 335–348. https://doi.org/10.1177/1464884910392851 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  5. Banholzer, V. M. (2015). Das Politische des Technikjournalismus. Zur gesellschaftlichen Bedeutung ganzheitlicher Technikberichterstattung in Massenmedien. [The political of technology journalism.] Schriftenreihe der Technischen Hochschule Nürnberg Georg Simon Ohm, 3–38. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  6. Bareis, J., & Katzenbach, C. (2022). Talking AI into being: The narratives and imaginaries of national AI strategies and their performative politics. Science, Technology, & Human Values, 47(5), 855–881. https://doi.org/10.1177/01622439211030007 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  7. Bartsch, A., Neuberger, C., Stark, B., Karnowski, V., Maurer, M., Pentzold, C., Quandt, T., Quiring, O., & Schemer, C. (2024). Epistemic authority in the digital public sphere. An integrative conceptual framework and research agenda. Communication Theory. https://doi.org/10.1093/ct/qtae020 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  8. Beck, U. (2003 [1998]). Politics of risk society. In D. Pepper, F. Webster, & G. Revill, Environmentalism. Critical concepts (pp. 256–266). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  9. Beckers, K., & Van Aelst, P. (2019). Look who’s talking: An analysis of actors in television news (2003–2016). Journalism Studies, 20(6), 872–890. https://doi.org/10.1080/1461670X.2018.1463169 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  10. Bengio, Y., Russell, S., Selman, B., Musk, E., Wozniak, S., Harari, Y. N., Mostaque, E., Yang, A., & 33.706 signees (2023, March 22). Pause giant AI experiments: An open letter. Future of Life Institute. Retrieved December 2024, from https://futureoflife.org/open-letter/pause-giant-ai-experiments/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  11. Bogner, A., Littig, B., & Menz, W. (2014). Wer ist ein Experte? Wissenssoziologische Grundlagen des Expertinneninterviews. [Who is an expert?] In A. Bogner, B. Littig, & W. Menz, Interviews mit Experten (pp. 9–15). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-531-19416-5_2 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  12. Boyce, T. (2006). Journalism and expertise. Journalism Studies, 7(6), 889–906. https://doi.org/10.1080/14616700600980652 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  13. Boykoff, J. (2012). US media coverage of the Cancún climate change conference. PS: Political Science & Politics, 45(2), 251–258. https://doi.org/10.1017/S104909651100206X Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  14. Brantner, C., & Saurwein, F. (2021). Covering technology risks and responsibility: Automation, artificial intelligence, robotics, and algorithms in the media. International Journal of Communication, 15, 5074–5098. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  15. Brennen, J. S., Howard, P. N., & Nielsen, R. K. (2018). An industry-led debate: How UK media cover artificial intelligence (Oxford Martin Programme on Misinformation, Science and Media, pp. 1–10). Reuters Institute for the Study of Journalism. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  16. Brennen, J. S., Howard, P. N., & Nielsen, R. K. (2022). What to expect when you’re expecting robots: Futures, expectations, and pseudo-artificial general intelligence in UK news. Journalism, 23(1), 22–38. https://doi.org/10.1177/1464884920947535 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  17. Buz, C., Promies, N., Kohler, S., & Lehmkuhl, M. (2021). Validierung von NER-Verfahren zur automatisierten Identifikation von Akteuren in deutschsprachigen journalistischen Texten. [Validation of NER methods for the automated identification of actors in journalistic German texts.] Studies in Communication and Media, 10(4), 590–627. https://doi.org/10.5771/2192-4007-2021-4-590 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  18. Carvalho, A., & Burgess, J. (2005). Cultural circuits of climate change in the U.K. broadsheet newspapers, 1985–2003. Risk Analysis, 25(6), 1457–1469. https://doi.org/10.1111/j.1539-6924.2005.00692.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  19. Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2017). Artificial intelligence and the ‘Good Society’: The US, EU, and UK approach. Science and Engineering Ethics, 24, 505–528. https://doi.org/10.1007/s11948-017-9901-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  20. Chuan, C.-H., Tsai, W.-H. S., & Cho, S. Y. (2019). Framing artificial intelligence in American newspapers. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 339–344. https://doi.org/10.1145/3306618.3314285 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  21. Collins, H., & Evans, R. (2007). Rethinking expertise. University of Chicago Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  22. Collins, H., & Evans, R. (2015). Expertise revisited, part I – Interactional expertise. Studies in History and Philosophy of Science Part A, 54, 113–123. https://doi.org/10.1016/j.shpsa.2015.07.004 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  23. Collins, H., & Evans, R. (2018). A sociological/philosophical perspective on expertise: The acquisition of expertise through socialization. In K. A. Ericsson, R. R. Hoffman, A. Kozbelt, & A. M. Williams (Eds.), The Cambridge handbook of expertise and expert performance (2nd ed., pp. 21–32). Cambridge University Press. https://doi.org/10.1017/9781316480748.002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  24. Conrad, P. (1999). Uses of expertise: Sources, quotes, and voice in the reporting of genetics in the news. Public Understanding of Science, 8(4), 285–302. https://doi.org/10.1088/0963-6625/8/4/302 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  25. Cools, H., Van Grop, B., & Opgenhaffen, M. (2024). Where exactly between utopia and dystopia? A framing analysis of AI and automation in US newspapers. Journalism, 25(1), 3–21. https://doi.org/10.1177/14648849221122647 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  26. Fischer, S., & Puschmann, C. (2021). Wie Deutschland über Algorithmen schreibt. Eine Analyse des Mediendiskurses über Algorithmen und Künstliche Intelligenz (2005–2020). [How Germany writes about algorithms.] Bertelsmann Stiftung. Retrieved from https://www.bertelsmann-stiftung.de/fileadmin/files/user_upload/Diskursanalyse_2021_Algorithmen.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  27. Flynn, J. (2014). System and lifeworld in Habermas’ theory of democracy. Philosophy & Social Criticism, 40(2), 205–214. https://doi.org/10.1177/0191453713518326 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  28. Funtowicz, S. O., & Ravetz, J. R. (1994). Uncertainty, complexity and post-normal science. Environmental Toxicology and Chemistry, 13(12), 1881–1885. https://doi.org/10.1002/etc.5620131203 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  29. Galtung, J., & Ruge, M. H. (1965). The structure of foreign news: The presentation of the Congo, Cuba and Cyprus crises in four Norwegian newspapers. Journal of Peace Research, 2(1), 64–90. https://doi.org/10.1177/002234336500200104 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  30. Gamer, M., Lemon, J., Fellows, I., & Singh, P. (2019). irr: Various coefficients of interrater reliability and agreement (Version 0.84.1). https://doi.org/10.32614/CRAN.package.irr Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  31. Gärtner, L. (2023). Who builds the media agenda? Actors’ influence over German newspaper coverage of climate change. Universität Mannheim. Retrieved from https://nbn-resolving.org/urn:nbn:de:bsz:180-madoc-643362 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  32. Gerhards, J., & Neidhardt, F. (1990). Strukturen und Funktionen moderner Öffentlichkeit: Fragestellungen und Ansätze. [Structures and functions of the modern public.] WZB Discussion Paper, No. FS III, 90–101. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  33. Gerhards, J./Schäfer, M. S. (2009). Two normative models of science in the public sphere: human genome sequencing in German and US mass media. Public Understanding of Science, 18(4), 437–451. https://doi.org/10.1177/0963662507082891 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  34. Giddens, A. (1991). The consequences of modernity. Polity Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  35. Gläser, J., & Laudel, G. (2010). Experteninterviews und qualitative Inhaltsanalyse als Instrumente rekonstruierender Untersuchungen [Expert interviews and qualitative content analysis as instruments for reconstructing studies] (4th ed.). VS Verlag. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  36. Grunwald, A. (2019). The inherently democratic nature of technology assessment. Science and Public Policy, 46(5), 702–709. https://doi.org/10.1093/scipol/scz023 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  37. Habermas, J. (1998). Faktizität und Geltung: Beiträge zur Diskurstheorie des Rechts und des demokratischen Rechtsstaats [Between facts and norms] (1st ed.). Suhrkamp. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  38. Hagen, L. M. (1993). Opportune witnesses: An analysis of balance in the selection of sources and arguments in the leading German newspapers’ coverage of the census Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  39. issue. European Journal of Communication, 8(3), 317–343. https://doi.org/10.1177/0267323193008003004 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  40. Harroch, D. A., & Harroch, R. D. (2025, April 25). 15 quotes on the future of AI. Retrieved from https://www.allbusiness.com/quotes-on-the-future-of-ai Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  41. Hart, P. S., Chinn, S., & Soroka, S. (2020). Politicization and polarization in COVID-19 news coverage. Science Communication, 42(5), 679–697. https://doi.org/10.1177/1075547020950735 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  42. Hauser, C. (2013). Ein Teilerfolg der Nanowissenschaften? Eine Inhaltsanalyse zur Nanoberichterstattung in repräsentativen Medien Österreichs, Deutschlands und der Schweiz. [A partial success of nanosciences?]. http://doi.org/10.1553/ITA-ms-12-04 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  43. Henschel, A. (2023, November 7). Kommunizieren wir an der KI-Forschung vorbei? [Do we talk past the AI research?] wissenschaftskommunikation.de. Retrieved from https://www.wissenschaftskommunikation.de/kommunizieren-wir-an-der-ki-forschung-vorbei-72093/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  44. Huber, B. (2014). Öffentliche Experten: Über die Medienpräsenz von Fachleuten. [Public experts.] Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-05405-2 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  45. Kieslich, K., Došenović, P., & Marcinkowski, F. (2022). Everything, but hardly any science fiction: A topic analysis of German media coverage of AI. MeMo:KI, 7, 1–12. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  46. Kleemans, M., Schaap, G., & Hermans, L. (2017). Citizen sources in the news: Above and beyond the vox pop? Journalism, 18(4), 464–481. https://doi.org/10.1177/1464884915620206 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  47. Köstler, L., & Ossewaarde, R. (2022). The making of AI society: AI futures frames in German political and media discourses. AI & SOCIETY, 37(1), 249–263. https://doi.org/10.1007/s00146-021-01161-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  48. Krippendorff, K. (2004). Reliability in content analysis.: Some common misconceptions and recommendations. Human Communication Research, 30(3), 411–433. https://doi.org/10.1111/j.1468-2958.2004.tb00738.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  49. Laursen, B., & Trapp, N. L. (2021). Experts or advocates: Shifting roles of central sources used by journalists in news stories? Journalism Practice, 15(1), 1–18. https://doi.org/10.1080/17512786.2019.1695537 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  50. Lehmkuhl, M., & Leidecker-Sandmann, M. (2019). „Visible scientists revisited“: Zum Zusammenhang von wissenschaftlicher Reputation und der Präsenz wissenschaftlicher Experten in der Medienberichterstattung über Infektionskrankheiten. [„Visible scientists revisited“: The correlation between scientific reputation and the presence of scientific experts in the media coverage of infectious diseases.] Publizistik, 64(4), 479–502. https://doi.org/10.1007/s11616-019-00530-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  51. Leidecker-Sandmann, M., Attar, P., Schütz, A., & Lehmkuhl, M. (2022). Selected by expertise? Scientific experts in German news coverage of COVID-19 compared to other pandemics. Public Understanding of Science, 31(7), 847–866. https://doi.org/10.1177/09636625221095740 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  52. Leidecker-Sandmann, M., & Lehmkuhl, M. (2022). Politisierung oder Aufklärung? Analysen der Akteur:innen- und Aussagenstruktur in medialen Diskursen über gesundheitliche Risikophänomene und die Rolle wissenschaftlicher Expert:innen. [Politicisation or enlightenment?] Studies in Communication and Media, 11(3), 337–393. https://doi.org/10.5771/2192-4007-2022-3-337 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  53. Luhmann, N. (1987). Die Differenzierung von Politik und Wirtschaft und ihre gesellschaftlichen Grundlagen. [The differentiation of politics and economy and its social basis.] In N. Luhmann, Soziologische Aufklärung 4: Beiträge zur funktionalen Differenzierung der Gesellschaft (pp. 32–48). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-663-01341-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  54. Jasanoff, S., & Kim, S.-H. (2009). Containing the atom: Sociotechnical imaginaries and nuclear power in the United States and South Korea. Minerva, 47(2), 119–146. https://doi.org/10.1007/s11024-009-9124-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  55. Marcinkowski, F., & Flaßhoff, F. G. (2024). Exploring the common wisdom on artificial intelligence and its political consequences. In M. W. Bauer & B. Schiele (Eds.). AI and common sense. Ambitions and frictions (pp. 127–142). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  56. Meyer, M. (2010). The rise of the knowledge broker. Science Communication, 32(1), 118–127. https://doi.org/10.1177/1075547009359797 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  57. Milde, J., & Ruhrmann, G. (2006). Molekulare Medizin in deutschen TV-Wissenschaftsmagazinen. Ergebnisse von Journalisteninterviews und Inhaltsanalysen. [Molecular medicine in German TV science magazines.] Medien & Kommunikationswissenschaft, 54(3), 430–456. https://doi.org/10.5771/1615-634x-2006-3-430 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  58. Moore, A., & Stilgoe, J. (2009). Experts and anecdotes: The role of “anecdotal evidence” in public scientific controversies. Science, Technology, & Human Values, 34(5), 654–677. https://doi.org/10.1177/0162243908329382 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  59. Mustaklem, M. (2024). What’s wrong with the robots? An Oxford researcher explains how we can better illustrate AI news stories [Interview by Adami, M.]. Reuters Institute for the Study of Journalism. Reuters Institute. Retrived from https://reutersinstitute.politics.ox.ac.uk/news/whats-wrong-robots-oxford-researcher-explains-how-we-can-better-illustrate-ai-news-stories Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  60. Neuberger, C., Bartsch, A., Reinemann, C., Fröhlich, R., Hanitzsch, T., & Schindler, J. (2019). Der digitale Wandel der Wissensordnung. Theorierahmen für die Analyse von Wahrheit, Wissen und Rationalität in der öffentlichen Kommunikation. [The digital transformation of the knowledge order.] Medien & Kommunikationswissenschaft, 67(2), 167–186. https://doi.org/10.5771/1615-634X-2019-2-167 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  61. Nguyen, D., & Hekman, E. (2022). The news framing of artificial intelligence: A critical exploration of how media discourses make sense of automation. AI & SOCIETY, 39. https://doi.org/10.1007/s00146-022-01511-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  62. Niemi, M. K., & Pitkänen, V. (2017). Gendered use of experts in the media: Analysis of the gender gap in Finnish news journalism. Public Understanding of Science, 26(3), 355–368. https://doi.org/10.1177/0963662515621470 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  63. Nisbet, M. C., & Lewenstein, B. V. (2002). Biotechnology and the American media: The policy process and the elite press, 1970 to 1999. Science Communication, 23(4), 359–391. https://doi.org/10.1177/107554700202300401 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  64. Nölleke, D. (2009). Die Konstruktion von Expertentum im Journalismus. [The construction of expertise in journalism.] In B. Dernbach & T. Quandt (Eds.), Spezialisierung im Journalismus (pp. 97–110). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-531-91582-1_7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  65. Nölleke, D. (2013). Experten im Journalismus: Systemtheoretischer Entwurf und empirische Bestandsaufnahme [Experts in journalism.] (1st ed.). Nomos. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  66. Ouchchy, L., Coin, A., & Dubljević, V. (2020). AI in the headlines: The portrayal of the ethical issues of artificial intelligence in the media. AI & SOCIETY, 35(4), 927–936. https://doi.org/10.1007/s00146-020-00965-5 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  67. Pedersen, T. L. (2024). patchwork: The composer of plots (Version 1.2.0, p. 1.2.0) [Dataset]. https://doi.org/10.32614/CRAN.package.patchwork Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  68. Peters, H. P. (1994). Wissenschaftliche Experten in der öffentlichen Kommunikation über Technik, Umwelt und Risiken. [Scientific experts in the public communication about technology, environment, and risks.] In F. Neidhardt (Ed.), Öffentlichkeit, öffentliche Meinung, soziale Bewegungen. Sonderheft 34 der Kölner Zeitschrift für Soziologie und Sozialpsychologie (pp. 162–190). Westdeutscher Verlag. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  69. Peters, H. P. (2014). Scientists as public experts. In M. Bucchi & B. Trench (Eds.), Routledge handbook of public communication of science and technology (2nd ed., pp. 70–82). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  70. Priaulx, N., Weinel, M., & Wrigley, A. (2016). Rethinking moral expertise. Health Care Analysis, 24(4), 393–406. https://doi.org/10.1007/s10728-014-0282-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  71. R Core Team. (2023). R: A language and environment for statistical computing (Version 4.3.2). R Foundation for Statistical Computing. https://www.R-project.org/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  72. Reed, M. I. (1996). Expert power and control in late modernity: An empirical review and theoretical synthesis. Organization Studies, 17(4), 573–597. https://doi.org/10.1177/017084069601700402 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  73. Roßmann, M. (2021). Vision as make-believe: How narratives and models represent sociotechnical futures. Journal of Responsible Innovation, 8(1), 70–93. https://doi.org/10.1080/23299460.2020.1853395 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  74. Rotolo, D., Hicks, D., & Martin, B. R. (2015). What is an emerging technology? Research Policy, 44(10), 1827–1843. https://doi.org/10.1016/j.respol.2015.06.006 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  75. Ryazanov, I., Öhman, C., & Björklund, J. (2024). How ChatGPT changed the media’s narratives on AI: A semi-automated narrative analysis through frame semantics. Minds and Machines, 35(1), 2. https://doi.org/10.1007/s11023-024-09705-w Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  76. Schäfer, M. S. (2009). From public understanding to public engagement: An empirical assessment of changes in science coverage. Science Communication, 30(4), 475–505. https://doi.org/10.1177/1075547008326943 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  77. Scharkow, M. (2012). Automatische Inhaltsanalyse und maschinelles Lernen. [Automated content analysis and machine learning.] epubli. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  78. Scheufele, B., & Engelmann, I. (2013). Die publizistische Vermittlung von Wertehorizonten der Parteien: Normatives Modell und empirische Befunde zum Value-Framing und News Bias der Qualitäts- und Boulevardpresse bei vier Bundestagswahlen. [The journalistic communication of parties’ value horizons: Normative model and empirical findings on value framing and news bias in quality and tabloid press during four federal elections.] Medien & Kommunikationswissenschaft, 61(4), 532–550. https://doi.org/10.5771/1615-634x-2013-4-532 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  79. Schimank, U. (2005). Die Entscheidungsgesellschaft. [The decision society.] VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-322-80606-2 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  80. Schneider, S. (2019). The takeover of science communication: How science lost its leading role in the public discourse on carbon capture and storage research in daily newspapers in Germany. Geoscience Communication, 2(1), 69–82. https://doi.org/10.5194/gc-2-69-2019 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  81. Signorell, A. (2024). DescTools: Tools for descriptive statistics (Version 0.99.54). https://doi.org/10.32614/CRAN.package.DescTools Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  82. Singer, P. (2006). Moral experts. In E. Selinger & R. P. Crease (Eds.), The philosophy of expertise (pp. 187–190). Columbia University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  83. Solomonoff, R. J. (1985). The time scale of artificial intelligence: Reflections on social effects. Human Systems Management, 5(2), 149–153. https://doi.org/10.3233/HSM-1985-5207 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  84. Steele, J. E. (1995). Experts and the operational bias of television news: The case of Persian Gulf War. Journalism & Mass Communication Quarterly, 72(4), 799–812. https://doi.org/10.1177/107769909507200404 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  85. Sun, S., Zhai, Y., Shen, B., & Chen, Y. (2020). Newspaper coverage of artificial intelligence: A perspective of emerging technologies. Telematics and Informatics, 53. https://doi.org/10.1016/j.tele.2020.101433 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  86. Takahashi, B. (2011). Framing and sources: A study of mass media coverage of climate change in Peru during V ALCUE. Public Understanding of Science, 20(4), 543–557. https://doi.org/10.1177/0963662509356502 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  87. Tavares, A. O., Areia, N. P., Mendes, J. M., & Pinto, H. (2022). The media coverage of climate change in Portugal. In A. N. Martins, G. Lizarralde, T. Egbelakin, L. Hobeica, J. M. Mendes, & A. Hobeica (Eds.), Investing in disaster risk reduction for resilience (pp. 237–256). Elsevier. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  88. Van Dijk, T. A. (2009). Discourse as interaction in society. In T. A. van Dijk (Ed.), Discourse as social interaction (Reprint, pp. 1–37). SAGE. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  89. Vergeer, M. (2020). Artificial intelligence in the Dutch press: An analysis of topics and trends. Communication Studies, 71(3), 373–392. https://doi.org/10.1080/10510974.2020.1733038 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  90. Vogelgesang, J., & Scharkow, M. (2012). Reliabilitätstests in Inhaltsanalysen: Eine Analyse der Dokumentationspaxis in Publizistik und Medien & Kommunikationswissenschaft. [Reliability tests in content analyses.] Publizistik, 57(3), 333–345. https://doi.org/10.1007/s11616-012-0154-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  91. Vrabič Dežman, D. (2024). Promising the future, encoding the past: AI hype and public media imagery. AI and Ethics, 4(3), 743–756. https://doi.org/10.1007/s43681-024-00474-x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  92. Weinstein, B. D. (1993). What is an expert? Theoretical Medicine, 14(1), 57–73. https://doi.org/10.1007/BF00993988 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  93. Weinstein, B. D. (1994). The possibility of ethical expertise. Theoretical Medicine, 15(1), 61–75. https://doi.org/10.1007/BF00999220 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  94. Wickham, H., Averick, M., Bryan, J., Chang, W., McGowan, L., François, R., Grolemund, G., Hayes, A., Henry, L., Hester, J., Kuhn, M., Pedersen, T., Miller, E., Bache, S., Müller, K., Ooms, J., Robinson, D., Seidel, D., Spinu, V., … Yutani, H. (2019). Welcome to the tidyverse. Journal of Open Source Software, 4(43). https://doi.org/10.21105/joss.01686 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  95. Zhai, Y., Yan, J., Zhang, H., & Lu, W. (2020). Tracing the evolution of AI: Conceptualization of artificial intelligence in mass media discourse. Information Discovery and Delivery, 48(3), 137–149. https://doi.org/10.1108/IDD-01-2020-0007 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  96. Zhu, H. (2021). kableExtra:Construct complex table with ‘kable’ and pipe syntax (Version 1.3.4). https://doi.org/10.32614/CRAN.package.kableExtra Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  97. Zorthian, J. (2023, May 16). OpenAI CEO Sam Altman asks congress to regulate AI. Retrieved from https://time.com/6280372/sam-altman-chatgpt-regulate-ai/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  98.   Open Google Scholar DOI: 10.5771/2192-4007-2026-2-006
  99. Abraído-Lanza, A. F., Shelton, R. C., Martins, M. C., & Crookes, D. M. (2017). Social norms, acculturation, and physical activity among Latina women. Journal of Immigrant and Minority Health, 19(2), 285–293. https://doi.org/10.1007/s10903-016-0519-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  100. Aira, T., Vasankari, T., Heinonen, O. J., Korpelainen, R., Kotkajuuri, J., Parkkari, J., Savonen, K., Uusitalo, A., Valtonen, M., Villberg, J., Vähä-Ypyä, H., & Kokko, S. P. (2021). Physical activity from adolescence to young adulthood: Patterns of change, and their associations with activity domains and sedentary time. International Journal of Behavioral Nutrition and Physical Activity, 18(85). https://doi.org/10.1186/s12966-021-01130-x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  101. Aubert, S., Brazo-Sayavera, J., González, S. A., Janssen, I., Manyanga, T., Oyeyemi, A. L., Picard, P., Sherar, L. B., Turner, E., & Tremblay, M. S. (2021). Global prevalence of physical activity for children and adolescents; inconsistencies, research gaps, and recommendations: A narrative review. International Journal of Behavioral Nutrition and Physical Activity, 18(1). https://doi.org/10.1186/s12966-021-01155-2 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  102. Ball, K., Jeffery, R. W., Abbott, G., McNaughton, S. A., & Crawford, D. (2010). Is healthy behavior contagious? Associations of social norms with physical activity and healthy eating. International Journal of Behavioral Nutrition and Physical Activity, 7(1), 86. https://doi.org/10.1186/1479-5868-7-86 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  103. Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Pearson Prentice Hall. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  104. Bernhard, U., & Dohle, M. (2018). Perceptual processes and political participation: Do the presumed reach and the presumed influence of social media affect political activities via Facebook and Twitter? Communications, 43(4), 451–467. https://doi.org/10.1515/commun-2017-0052 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  105. Blue, C. L., Wilbur, J., & Marston-Scott, M. (2001). Exercise among blue-collar workers: Application of the theory of planned behavior. Research in Nursing & Health, 24(6), 481–493. https://doi.org/10.1002/nur.10008 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  106. Buda, G., Lukoševičiūtė, J., Šalčiūnaitė, L., & Šmigelskas, K. (2021). Possible effects of social media use on adolescent health behaviors and perceptions. Psychological Reports, 124(3), 1031–1048. https://doi.org/10.1177/0033294120922481 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  107. Bundesamt für Statistik. (2022). Statistik der Bildungsinstitutionen (SBI) [Statistic of the education institutions] (No. SJ 2021/22). Bundesamt für Statistik. https://www.bfs.admin.ch/bfs/de/home/statistiken/bildung-wissenschaft/bildungsinstitutionen.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  108. Carson, V., & Spence, J. C. (2010). Seasonal variation in physical activity among children and adolescents: A review. Pediatric Exercise Science, 22(1), 81–92. https://doi.org/10.1123/pes.22.1.81 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  109. Chen, F. (2007). Sensitivity of goodness of fit indexes to lack of measurement invariance. Structural Equation Modeling, 14(3), 464–504. https://doi.org/10.1080/10705510701301834 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  110. Cheng, Y., & Chen, Z. F. (2020). The influence of presumed fake news influence: Examining public support for corporate corrective response, media literacy interventions, and governmental regulation. Mass Communication and Society, 23(5), 705–729. https://doi.org/10.1080/15205436.2020.1750656 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  111. Chia, S. C. (2006). How peers mediate media influence on adolescents’ sexual attitudes and sexual behavior. Journal of Communication, 56(3), 585–606. https://doi.org/10.1111/j.1460-2466.2006.00302.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  112. Chia, S. C., & Wen, N. (2010). College men’s third-person perceptions about idealized body image and consequent behavior. Sex Roles, 63(7), 542–555. https://doi.org/10.1007/s11199-010-9833-z Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  113. Cho, H., Shen, L., & Peng, L. (2021). Examining and extending the influence of presumed influence hypothesis in social media. Media Psychology, 24(3), 413–435. https://doi.org/10.1080/15213269.2020.1729812 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  114. Chung, A. C. A., & Rimal, R. N. (2016). Social norms: A review. Review of Communication Research, 4(1), 1–28. https://doi.org/10.12840/issn.2255-4165.2016.04.01.008 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  115. Cialdini, R. B., Reno, R. R., & Kallgren, C. A. (1990). A focus theory of normative conduct: Recycling the concept of norms to reduce littering in public places. Journal of Personality and Social Psychology, 58(6), 1015–1026. https://doi.org/10.1037/0022-3514.58.6.1015 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  116. Davis, J. P., Pedersen, E. R., Tucker, J. S., Dunbar, M. S., Seelam, R., Shih, R., & D’Amico, E. J. (2019). Long-term associations between substance use-related media exposure, descriptive norms, and alcohol use from adolescence to young adulthood. Journal of Youth and Adolescence, 48(7), 1311–1326. https://doi.org/10.1007/s10964-019-01024-z Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  117. Davison, W. P. (1983). The third-person effect in communication. The Public Opinion Quarterly, 47(1), 1–15. https://doi.org/10.1086/268763 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  118. Dohle, M., Bernhard, U., & Kelm, O. (2017). Presumed media influences and demands for restrictions: Using panel data to examine the causal direction. Mass Communication and Society, 20(5), 595–613. https://doi.org/10.1080/15205436.2017.1303072 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  119. Dormann, C., & Griffin, M. A. (2015). Optimal time lags in panel studies. Psychological Methods, 20(4), 489–505. https://doi.org/10.1037/met0000041 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  120. Dumith, S. C., Gigante, D. P., Domingues, M. R., & Kohl, H. W., III. (2011). Physical activity change during adolescence: A systematic review and a pooled analysis. International Journal of Epidemiology, 40(3), 685–698. https://doi.org/10.1093/ije/dyq272 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  121. Dunlop, S., Freeman, B., & Jones, S. C. (2016). Marketing to youth in the digital age: The promotion of unhealthy products and health promoting behaviours on social media. Media and Communication, 4(3), 35–49. https://doi.org/10.17645/mac.v4i3.522 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  122. Durau, J., Diehl, S., & Terlutter, R. (2024). Working (out) with fitness influencers – Benefits for the fitness influencer, user health, and the endorsed brand: Key factors and the role of gender and brand familiarity. Digital Health, 2024(10). https://doi.org/10.1177/20552076241258393 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  123. Easton, S., Morton, K., Tappy, Z., Francis, D., & Dennison, L. (2018). Young people’s experiences of viewing the fitspiration social media trend: Qualitative study. Journal of Medical Internet Research, 20(6). https://doi.org/10.2196/jmir.9156 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  124. Fitzgerald, A., Fitzgerald, N., & Aherne, C. (2012). Do peers matter? A review of peer and/or friends’ influence on physical activity among American adolescents. Journal of Adolescence, 35(4), 941–958. https://doi.org/10.1016/j.adolescence.2012.01.002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  125. Folk, A., & Kovacs, S. (2021). Social media use and physical activity participation in college students: An exploratory analysis. CommonHealth, 2(3). https://doi.org/10.15367/ch.v2i3.492 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  126. Frey, T., & Friemel, T. N. (2021). Substanzkonsum unter Jugendlichen und jungen Erwachsenen in der Schweiz im Jahr 2021: Eine repräsentative Befragung unter 15-bis 19-Jährigen [Substance consumption of adolescents and young adults in Switzerland in 2021: A representative survey of 15 to 19 year olds]. Universität Zürich. https://doi.org/10.5167/uzh-211166 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  127. Geusens, F., & Beullens, K. (2021). Perceptions surpass reality: Self-reported alcohol-related communication on Instagram is more strongly related with frequency of alcohol consumption and binge drinking than actual alcohol-related communication. Drug and Alcohol Dependence, 227. https://doi.org/10.1016/j.drugalcdep.2021.109004 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  128. Gonzalez, M. D. (2023, June 07). Die Social-Media-Nutzung von Jugendlichen in Deutschland: Trends und Gewohnheiten [Social media use among young people in Germany: Trends and habits]. Digimind Blog. https://web.archive.org/web/20260208054603/https://blog.digimind.com/de/social-media-nutzung-von-jugendlichen-in-deutschland Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  129. Goodyear, V. A., Boardley, I., Chiou, S.-Y., Fenton, S. A. M., Makopoulou, K., Stathi, A., Wallis, G. A., Veldhuijzen van Zanten, J. J. C. S., & Thompson, J. L. (2021). Social media use informing behaviours related to physical activity, diet and quality of life during COVID-19: A mixed methods study. BMC Public Health, 21(1). https://doi.org/10.1186/s12889-021-11398-0 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  130. Goodyear, V. A., Boardley, I., Chiou, S.-Y., Fenton, S. A. M., Makopoulou, K., Stathi, A., Wallis, G. A., Veldhuijzen van Zanten, J. J. C. S., Wood, G. E. R., & Thompson, J. L. (2021). Guidelines for using social media to inform behaviours related to physical activity, diet and quality of life. University of Birmingham. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  131. Greyling, C., & Naud, L. (2023). The fitspiration-effect: Fitness identity of emerging adult females on social media. South African Journal for Research in Sport, Physical Education and Recreation, 45(2), 28–45. https://doi.org/10.36386/sajrsper.v45i2.96 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  132. Griep, Y., Vranjes, I., Kraak, J. M., Dudda, L., & Li, Y. (2021). Start small, not random: Why does justifying your time-lag matter? The Spanish Journal of Psychology, 24. https://doi.org/10.1017/SJP.2021.42 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  133. Gunther, A. C. (1998). The persuasive press inference: Effects of mass media on perceived public opinion. Communication Research, 25(5), 486–504. https://doi.org/10.1177/009365098025005002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  134. Gunther, A. C., Bolt, D., Borzekowski, D. L. G., Liebhart, J. L., & Dillard, J. P. (2006). Presumed influence on peer norms: How mass media indirectly affect adolescent smoking. Journal of Communication, 56(1), 52–68. https://doi.org/10.1111/j.1460-2466.2006. 00002.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  135. Gunther, A. C., & Storey, J. D. (2003). The influence of presumed influence. Journal of Communication, 53(2), 199–215. https://doi.org/10.1111/j.1460-2466.2003.tb02586.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  136. Günther, L., Schleberger, S., & Pischke, C. R. (2021). Effectiveness of social media-based interventions for the promotion of physical activity: Scoping review. International Journal of Environmental Research and Public Health, 18(24). https://doi.org/10.3390/ijerph182413018 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  137. Hamaker, E. L., Kuiper, R. M., & Grasman, R. P. P. P. (2015). A critique of the cross-lagged panel model. Psychological Methods, 20(1), 102–116. https://doi.org/10.1037/a0038889 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  138. Ho, S. S., Lee, E. W. J., Ng, K., Leong, G. S. H., & Tham, T. H. M. (2016). For fit’s sake: A norms-based approach to healthy behaviors through influence of presumed media influence. Health Communication, 31(9), 1072–1080. https://doi.org/10.1080/10410236.2015.1038772 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  139. Ho, S. S., Poorisat, T., Neo, R. L., & Detenber, B. H. (2014). Examining how presumed media influence affects social norms and adolescents’ attitudes and drinking behavior intentions in rural Thailand. Journal of Health Communication, 19(3), 282–302. https://doi.org/10.1080/10810730.2013.811329 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  140. Hong, Y., & Kim, S. (2020). Influence of presumed media influence for health prevention: How mass media indirectly promote health prevention behaviors through descriptive norms. Health Communication, 35(14), 1800–1810. https://doi.org/10.1080/10410236.2019.1663585 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  141. Hu, L., & Bentler, P. M. (1995). Evaluating model fit. In R. H. Hoyle (Ed.), Structural equation Modeling. Concepts, issues, and applications (pp. 76–99). Sage. https://us.sagepub.com/en-us/nam/structural-equation-modeling/book4796 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  142. Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1–55. https://doi.org/10.1080/10705519909540118 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  143. Jacobson, R. P., Mortensen, C. R., Jacobson, K. J. L., & Cialdini, R. B. (2015). Self-control moderates the effectiveness of influence attempts highlighting injunctive social norms. Social Psychological and Personality Science, 6(6), 718–726. https://doi.org/10.1177/1948550615578463 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  144. Jerónimo, F., & Carraça, E. V. (2022). Effects of fitspiration content on body image: A systematic review. Eating and Weight Disorders – Studies on Anorexia, Bulimia and Obesity, 27(8), 3017–3035. https://doi.org/10.1007/s40519-022-01505-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  145. Johns, D. J., Langley, T. E., & Lewis, S. (2017). Use of social media for the delivery of health promotion on smoking, nutrition, and physical activity: A systematic review. The Lancet, 390. https://doi.org/10.1016/S0140-6736(17)32984-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  146. Kim, J., Dunn, E., Rellinger, K., Robertson-Wilson, J., & Eys, M. (2019). Social norms and physical activity in American and Canadian contexts: A scoping review. International Review of Sport and Exercise Psychology, 12(1), 26–48. https://doi.org/10.1080/1750984X.2017.1354229 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  147. Külling-Knecht, C., Waller, G., Willemse, I., Deda-Bröchin, S., Suter, L., Streule, P., Settegrana, N., Jochim, M., Bernath, J., & Daniel, S. (2024). JAMES – Jugend, Aktivitäten, Medien – Erhebung Schweiz [JAMES – Youth, Activities, Media – Survey Switzerland]. Zürcher Hochschule für Angewandte Wissenschaften. https://www.zhaw.ch/de/psychologie/forschung/medienpsychologie/mediennutzung/james Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  148. Lapinski, M. K., & Rimal, R. N. (2005). An explication of social norms. Communication Theory, 15(2), 127–147. https://doi.org/10.1111/j.1468-2885.2005.tb00329.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  149. Lu, F. J. H., Hsu, Y.-W., Wang, E. T. W., Lin, J.-H., Chou, C.-C., & Yeh, L.-C. (2014). Adolescents’ physical activities and peer norms: The mediating role of self-efficacy. Perceptual and Motor Skills, 118(2), 362–374. https://doi.org/10.2466/06.30.PMS.118k23w3 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  150. Mackinnon, S., Curtis, R., & O’Connor, R. (2022). Tutorial in longitudinal measurement invariance and cross-lagged panel models using lavaan. Meta-Psychology, 6, 1–20. https://doi.org/10.15626/MP.2020.2595 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  151. Marsh, H. W., Hau, K.-T., & Wen, Z. (2004). In search of golden rules: Comment on hypothesis-testing approaches to setting cutoff values for fit indexes and dangers in overgeneralizing Hu and Bentler’s (1999) findings. Structural Equation Modeling: A Multidisciplinary Journal, 11(3), 320–341. https://doi.org/10.1207/s15328007sem1103_2 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  152. Maxwell, K. A. (2002). Friends: The role of peer influence across adolescent risk behaviors. Journal of Youth and Adolescence, 31(4), 267–277. https://doi.org/10.1023/A:10154 93316865 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  153. Mullen, B., Atkins, J. L., Champion, D. S., Edwards, C., Hardy, D., Story, J. E., & Vanderklok, M. (1985). The false consensus effect: A meta-analysis of 115 hypothesis tests. Journal of Experimental Social Psychology, 21(3), 262–283. https://doi.org/10.1016/0022-1031(85)90020-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  154. Nilsen, S. A., Stormark, K. M., Heradstveit, O., & Breivik, K. (2023). Trends in physical health complaints among adolescents from 2014 – 2019: Considering screen time, social media use, and physical activity. SSM – Population Health, 22. https://doi.org/10.1016/j.ssmph.2023.101394 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  155. Paek, H.-J., & Gunther, A. C. (2007). How peer proximity moderates indirect media influence on adolescent smoking. Communication Research, 34(4), 407–432. https://doi.org/10.1177/0093650207302785 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  156. Paek, H.-J., Gunther, A. C., McLeod, D. M., & Hove, T. (2011). How adolescents’ perceived media influence on peers affects smoking decisions. Journal of Consumer Affairs, 45(1), 123–146. https://doi.org/10.1111/j.1745-6606.2010.01195.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  157. Park, S.-Y. (2005). The influence of presumed media influence on women’s desire to be thin. Communication Research, 32(5), 594–614. https://doi.org/10.1177/0093650205279350 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  158. Patton, G. C., Sawyer, S. M., Santelli, J. S., Ross, D. A., Afifi, R., Allen, N. B., Arora, M., Azzopardi, P., Baldwin, W., Bonell, C., Kakuma, R., Kennedy, E., Mahon, J., McGovern, T., Mokdad, A. H., Patel, V., Petroni, S., Reavley, N., Taiwo, K., … Viner, R. M. (2016). Our future: A Lancet commission on adolescent health and wellbeing. Lancet (London, England), 387(10036), 2423–2478. https://doi.org/10.1016/S0140-6736(16)00579-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  159. Perry, A. S., Dooley, E. E., Master, H., Spartano, N. L., Brittain, E. L., & Pettee Gabriel, K. (2023). Physical activity over the lifecourse and cardiovascular disease. Circulation Research, 132(12), 1725–1740. https://doi.org/10.1161/CIRCRESAHA.123.322121 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  160. Pretorius, C., McCashin, D., & Coyle, D. (2022). Mental health professionals as influencers on TikTok and Instagram: What role do they play in mental health literacy and help-seeking? Internet Interventions, 30. https://doi.org/10.1016/j.invent.2022.100591 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  161. Priebe, C. S., & Spink, K. S. (2011). When in Rome: Descriptive norms and physical activity. Psychology of Sport and Exercise, 12(2), 93–98. https://doi.org/10.1016/j.psychsport.2010.09.001 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  162. Priebe, C. S., & Spink, K. S. (2012). Using messages promoting descriptive norms to increase physical activity. Health Communication, 27(3), 284–291. https://doi.org/10.1080/10410236.2011.585448 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  163. Prinstein, M. J., Boergers, J., & Spirito, A. (2001). Adolescents’ and their friends’ health-risk behavior: Factors that alter or add to peer influence. Journal of Pediatric Psychology, 26(5), 287–298. https://doi.org/10.1093/jpepsy/26.5.287 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  164. R Core Team. (2024). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  165. Rimal, R. N., & Lapinski, M. K. (2015). A re-explication of social norms, ten years later. Communication Theory, 25(4), 393–409. https://doi.org/10.1111/comt.12080 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  166. Rimal, R. N., & Real, K. (2005). How behaviors are influenced by perceived norms: A test of the theory of normative social behavior. Communication Research, 32(3), 389–414. https://doi.org/10.1177/0093650205275385 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  167. Robinson, E., Otten, R., & Hermans, R. C. J. (2016). Descriptive peer norms, self-control and dietary behaviour in young adults. Psychology & Health, 31(1), 9–20. https://doi.org/10.1080/08870446.2015.1067705 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  168. Rosseel, Y. (2011). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. https://doi.org/10.18637/jss.v048.i02 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  169. Rutter, L. A., Thompson, H. M., Howard, J., Riley, T. N., Jesús-Romero, R. D., & Lorenzo-Luaces, L. (2021). Social media use, physical activity, and internalizing symptoms in adolescence: Cross-sectional analysis. JMIR Mental Health, 8(9). https://doi.org/10.2196/26134 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  170. Santtila, M., Grönqvist, K., Räisänen, J., & Kyröläinen, H. (2014). Impact on physical fitness of exercise promotion service utilizing social media. Biomedical Human Kinetics, 6(1), 84–89. https://doi.org/10.2478/bhk-2014-0015 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  171. Sanzari, C. M., Gorrell, S., Anderson, L. M., Reilly, E. E., Niemiec, M. A., Orloff, N. C., Anderson, D. A., & Hormes, J. M. (2023). The impact of social media use on body image and disordered eating behaviors: Content matters more than duration of exposure. Eating Behaviors, 49. https://doi.org/10.1016/j.eatbeh.2023.101722 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  172. Scherbaum, C. A., Pesner, E., Humphrey, S. E., & LeBreton, J. M. (2019). Power analysis for multilevel research. In The handbook of multilevel theory, measurement, and analysis (pp. 329–352). American Psychological Association. https://doi.org/10.1037/0000115-015 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  173. Schwarz, N. (2008). The psychology of survey response. In W. Donsbach & M. Traugott (Eds.), The SAGE Handbook of Public Opinion Research (pp. 374–387). SAGE Publications Ltd. https://doi.org/10.4135/9781848607910.n35 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  174. Shimoga, S. V., Erlyana, E., & Rebello, V. (2019). Associations of social media use with physical activity and sleep adequacy among adolescents: Cross-sectional survey. Journal of Medical Internet Research, 21(6). https://doi.org/10.2196/14290 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  175. Shulman, H. C., & Levine, T. R. (2012). Exploring social norms as a group-level phenomenon: Do political participation norms exist and influence political participation on college campuses? Journal of Communication, 62(3), 532–552. https://doi.org/10.1111/j.1460-2466.2012.01642.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  176. Sokolova, K., & Perez, C. (2021). You follow fitness influencers on YouTube. But do you actually exercise? How parasocial relationships, and watching fitness influencers, relate to intentions to exercise. Journal of Retailing and Consumer Services, 58. https://doi.org/10.1016/j.jretconser.2020.102276 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  177. Spink, K. S., Crozier, A. J., & Robinson, B. (2013). Examining the relationship between descriptive norms and perceived effort in adolescent athletes: Effects of different reference groups. Psychology of Sport and Exercise, 14(6), 813–818. https://doi.org/10.1016/j.psychsport.2013.06.006 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  178. Steinberg, L., & Monahan, K. C. (2007). Age differences in resistance to peer influence. Developmental Psychology, 43(6), 1531–1543. https://doi.org/10.1037/0012-1649.43.6.1531 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  179. Strain, T., Flaxman, S., Guthold, R., Semenova, E., Cowan, M., Riley, L. M., Bull, F. C., & Stevens, G. A. (2024). National, regional, and global trends in insufficient physical activity among adults from 2000 to 2022: A pooled analysis of 507 population-based surveys with 5·7 million participants. The Lancet Global Health, 12(8), e1232–e1243. https://doi.org/10.1016/S2214-109X(24)00150-5 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  180. Sukamto, M., Hamidah, H., & Fajrianthi, F. (2019). “Can I look like her?”: Body image of adolescent girls who use social media. Makara Human Behavior Studies in Asia, 23(1), 60–72. https://doi.org/10.7454/hubs.asia.1120519 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  181. Tal-Or, N., Cohen, J., Tsfati, Y., & Gunther, A. C. (2010). Testing causal direction in the influence of presumed media influence. Communication Research, 37(6), 801–824. https://doi.org/10.1177/0093650210362684 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  182. Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110. https://doi.org/10.1037/h0031322 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  183. Vandenbosch, L., Beullens, K., Vanherle, V., Robyn, & Schreurs, L. (2025). Digital media uses and effects: The contributing roles of time. Journal of Children and Media, 19(1), 71–76. https://doi.org/10.1080/17482798.2024.2438690 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  184. Vandenbosch, L., Fardouly, J., & Tiggemann, M. (2022). Social media and body image: Recent trends and future directions. Current Opinion in Psychology, 45. https://doi.org/10.1016/j.copsyc.2021.12.002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  185. Wang, M. N., & Jiang, C. L. (2017). The expected and unexpected media effects on youth’s (mis)perceptions of peer norms: Chinese college students’ overestimation of peer smoking prevalence. Chinese Journal of Communication, 10(2), 115–133. https://doi.org/10.1080/17544750.2016.1202851 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  186. World Health Organization. (2018). Global action plan on physical activity 2018–2030: More active people for a healthier world. World Health Organization. https://iris.who.int/handle/10665/272722 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  187. World Health Organization. (2024). Physical activity [Fact sheet]. https://www.who.int/news-room/fact-sheets/detail/physical-activity Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  188. World Health Organization. (2025). Adolescent health. [WHO Health Topic]. https://www.who.int/health-topics/adolescent-health Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  189.   Open Google Scholar DOI: 10.5771/2192-4007-2026-2-007
  190. Aldrete, M. (2023). Challenging the protest paradigm and winning legitimacy. Analysis of the representation of the social movement against femicide in the mainstream media in Mexico. Current Sociology, 1–12. https://doi.org/10.1177/00113921231211578 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  191. Altman, D. G. (1991). Practical statistics for medical research. Taylor & Francis Ltd. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  192. BDZV (2024). Market data. https://www.bdzv.de/alle-themen/marktdaten Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  193. Betus, A., Kearns, E. M., & Lemieux, A. F. (2020). How perpetrator identity (sometimes) influences media framing attacks as “terrorism” or “mental illness”. Communication Research, 1–24. https://doi.org/10.1177/0093650220971142 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  194. Brill, J., Guenther, L., Ehrhardt, W., & Ruhrmann, G. (2021). Crime in television news: Do news factors predict the mentioning of a criminal’s country of origin? In J. B. Wiest (Ed.), Mass mediated representations of crime and criminality (pp. 31–48). Emerald Publishing. https://doi.org/10.1108/S2050-206020210000021008 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  195. Brill, J., Guenther, L., & Ruhrmann, G. (2025). Felons, right-wing extremists, foreign criminals, and Islamist terrorists: Frames of criminals in German television news. Journalism Practice, 19(4), 878–895. https://doi.org/10.1080/17512786.2023.2214127 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  196. Budde, N., Jandura, O., & Dohle, M. (2018). Das Framing der Flüchtlingskrise in Parlament und Parlamentsmagazinen [Framing of the refugee crisis in the parliament and parliament magazines]. Mitteilungen des Instituts für Deutsches und Internationales Parteienrecht und Parteienforschung (MIP), 24, 31–39. https://doi.org/10.25838/oaj-mip-201831-39 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  197. Conrey, S. C., & Haney, C. (2020). Framing of criminal justice and crime in the news: 2015–2017. Journal of Crime and Justice, 44(3), 297–315. https://doi.org/10.1080/0735648X.2020.1803102 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  198. Coleman, R. (2003). Race and ethical reasoning: The importance of race to journalistic decision making. Journalism & Mass Communication Quarterly, 80(2), 295–310. https://doi.org/10.1177/107769900308000205 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  199. Dan, V., & Ren, C. (2021). Understanding variations in the framing of people living with HIV: A mixed-methods study of photos in Chinese news. Journalism & Mass Communication Quarterly, 98(1), 200–220. https://doi.org/10.1177/1077699020984762 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  200. Dittrich, A., & Klimmt, C. (2020). Erwähnung der Täterherkunft in der Verbrechensberichterstattung: Welchen Effekt hat die populistische Medienschelte? [Mentioning the origin of perpetrators in crime reporting: What effect does populist media scolding have?]. Neue Kriminalpolitik, 33(1), 28–45. https://doi.org/10.5771/0934-9200-2021-1-28 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  201. Chong, D., & Druckman, J. N. (2007). Framing theory. Annual Review of Political Science, 10(10), 103–126. https://doi.org/10.1146/annurev.polisci.10.072805.103054 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  202. Eberl, J.-M., Meltzer, C. E., Heidenreich, T., Herrero, B., Theorin, N., Lind, F., Berganza, R., Boomgaarden, H. G., Schemer, C., & Strömbäck, J. (2018). The European media discourse on immigration and its effects: A literature review. Annals of the International Communication Association, 42(3), 207–223. https://doi.org/10.1080/ 23808985.2018. 1497452 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  203. Entman, R. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58. https://doi.org/10.1111/j.1460-2466.1993.tb01304.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  204. Federal Criminal Police Office (2025). Polizeiliche Kriminalstatistik 2024: Polizei registriert über 5,83 Millionen Straftaten im Jahr 2024 [Police crime statistics 2024: Over 5.83 million criminal offenses were recorded by the police in 2024]. https://www.bka.de/DE/AktuelleInformationen/StatistikenLagebilder/PolizeilicheKriminalstatistik/PKS2024/Polizeiliche_Kriminalstatistik_2024/Polizeiliche_Kriminalstatistik_2024_node.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  205. Federal Ministry of the Interior and Community (2025). Polizeiliche Kriminalstatistik [Police crime statistics]. https://www.bmi.bund.de/SharedDocs/downloads/DE/publikationen/themen/sicherheit/BMI25028_pks-2024.pdf?blob=publicationFile&v=4#page=12 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  206. Fengler, S., & Kreutler, M. (2020). Migration coverage in Europe’s media. A comparative analysis of coverage in 17 countries. Otto Brenner Stiftung. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  207. Ferrer-Conill, R., & Tandoc, E. C. (2018). The audience-oriented editor: Making sense of the audience in the newsroom. Digital Journalism, 6(4), 436–453. https://doi.org/10.1080/21670811.2018.1440972 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  208. Fleras, A. (2016). Theorizing minority misrepresentations. Reframing mainstream newsmedia as if white ethnic media. In G. Ruhrmann, Y. Shooman, & P. Widmann (Eds.), Media and minorities: Questions on representation from an international perspective (pp. 21–39). Vandenhoeck. https://doi.org/10.13109/9783666300882.21 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  209. Früh, W. (2017). Inhaltsanalyse: Theorie und Praxis [Content analysis: Theory and practice]. UVK. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  210. Gaddis, S. (2017). How black are Lakisha and Jamal? Racial perceptions from names used in correspondence audit studies. Sociological Science, 4, 469–489. https://doi.org/10.15195/v4.a19 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  211. Galtung, J., & Ruge, M. H. (1965). The structure of foreign news. Journal of Peace Research, 2(1), 64–90. https://doi.org/10.1177/002234336500200104 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  212. German Press Council (2017). Publizistische Grundsätze (Pressekodex). Richtlinien für die publizistische Arbeit nach den Empfehlungen des Deutschen Presserats. Beschwerde-ordnung [Journalistic principles (Press Code). Guidelines for journalistic work as recommended by the German Press Council. complaints procedure]. https://www.presserat.de/fileadmin/user_upload/Downloads_Dateien/Pressekodex2017_web.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  213. German Press Council (2024). Guiding principles for guideline 12.1. https://www.presserat.de/leitsaetze-zur-richtlinie-12-1.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  214. Goedeke Tort, M., Guenther, L., & Ruhrmann, G. (2016). Von kriminell bis willkommen. Wie die Herkunft über das mediale Framing von Einwanderern entscheidet [From criminal to welcome: How origin determines the media framing of immigrants]. Medien & Kommunikationswissenschaft, 64(4), 497–517. http://doi.org/10.5771/1615-634X-2016-4-497 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  215. Greer, C., & Reiner, R. (2015). Mediated mayhem: Media, crime and criminal justice. In M. Maguire, R. Morgan, & R. Reiner (Eds.), Oxford Handbook of Criminology (pp. 245–278). Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  216. Gruenewald, J., Chermak, S. M., & Pizarro, J. M. (2013). Covering victims in the news: What makes minority homicides newsworthy? Justice Quarterly, 30, 755–783. http://dx.doi.org/10.1080/07418825.2011.628945 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  217. Grygiel, J., & Lysak, S. (2020). Police social media and broadcast news: An investigation into the impact of police use of Facebook on journalists’ gatekeeping role. Journalism Practice, 15(7), 994–1011. https://doi.org/10.1080/17512786.2020.1759123 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  218. Jacobs, L. (2017). Patterns of criminal threat in television news coverage of ethnic minorities in Flanders (2003–2013), Journal of Ethnic and Migration Studies, 43(5), 809–829, https://doi.org/10.1080/1369183X.2016.1217152 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  219. Jewkes, Y. (2011). Media & Crime. Sage. http://doi.org/10.4236/jss.2019.74035 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  220. Klimmt, C., Dittrich, A., & Leuppert, R. (2024). Disclosure of perpetrator origin in crime news: Changing practices in journalism after populist accusations? Journalism, 26(2), 464–484. https://doi.org/10.1177/14648849241243191 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  221. Kort-Butler, L. A., & Habecker, P. (2018). Framing and cultivating the story of crime: The effects of media use, victimization, and social networks on attitudes about crime. Criminal Justice Review, 43(2), 127–146. https://doi.org/10.1177/0734016817710696 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  222. Krämer, B. (2017): Populist online practices: The function of the internet in right-wing populism. Information, Communication & Society, 20(9), 1293–1309. https://doi.org/10.1080/1369118X.2017.1328520 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  223. Kuhn, P., & Niewendick, M. (2024). Kriminalität in Deutschland. In diesen Regionen gibt es die meisten Straftaten [Crime in Germany. Most crime is committed in these regions]. https://www.welt.de/politik/deutschland/article196787711/Kriminalitaet-Im-Osten-auf-dem-Land-mehr-Straftaten-als-im-Westen.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  224. Kuckartz, U., & Rädiker, S. (2023). Qualitative content analysis: Methods, practice and software (2nd edition). SAGE. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  225. Landeskriminalamt Nordrhein-Westfalen (2024). Polizeiliche Kriminalstatistik Nordrhein-Westfalen 2023 [Police crime statistics North Rhine-Westphalia 2023]. https://polizei.nrw/sites/default/files/2024-10/pks_jahrbuch_2023.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  226. Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174. https://doi.org/10.2307/2529310 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  227. LaRose, J., Torres, J., & Barton, M. (2021). Changing media framings of school shootings: A case study of the Parkland school shooting. Journal of Mass Violence Research, 1(1), 44–61. https://doi.org/10.53076/JMVR11874 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  228. Lavie-Dinur, A., Karniel, Y., & Samuel-Azran, T. (2013). “Our” criminals – Israeli press coverage of domestic political criminals. Journal of Intercultural Communication Research, 42(3), 275–299. https://doi.org/10.1080/17475759.2013.822821 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  229. Lawler, A., & Tolley, E. (2017). Deciding what’s legitimate: Canadian news media framing of refugee admissions and settlement. International Journal of Communication, 11(2), 967–991. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  230. Lewis, J., Williams, A., & Franklin, B. (2008). A compromised fourth estate? UK news journalism, public relations and news sources. Journalism Studies, 9(1), 1–20. https://doi.org/10.1080/14616700701767974 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  231. Maier, M., Retzbach, J., Glogger, I., & Stengel, K. (2018). Nachrichtenwerttheorie [News value theory] (Vol. 2). Nomos. https://doi.org/10.5771/9783845284934 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  232. Matthes, J., & Kohring, M. (2004). Die empirische Erfassung von Medien-Frames [The empirical analysis of media frames]. Medien & Kommunikationswissenschaft, 52, 56–75. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  233. Matthes, J., & Kohring, M. (2008). The content analysis of media frames: Toward improving reliability and validity. Journal of Communication, 58, 258–279. https://doi.org/10.1111/j.1460-2466.2008.00384.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  234. Mayring, P. (2021). Qualitative content analysis: A step-by-step guide. SAGE Publications Ltd. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  235. Muncie, E. (2019). ‘Peaceful protesters’ and ‘dangerous criminals’: The framing and reframing of anti-fracking activists in the UK. Social Movement Studies, 19(4), 464–481. https://doi.org/10.1080/14742837.2019.1708309 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  236. O’Neill, D., & O’Connor, C. (2008). The passive journalist: How sources dominate local news. Journalism Practice, 2(3), 487–500. https://doi.org/10.1080/17512780802281248 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  237. Partain, L. P. B., & Weaver, A. J. (2022). (Un)Veiling our biases: Activating religious, emotional, and contextual cues in news media representations of Syrian refugees. International Journal of Communication, 16, 2410–2430. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  238. Polizeidirektion Osnabrück (2025). Polizeiliche Kriminalstatistik 2024 [Police crime statistics 2024]. https://www.pd-os.polizei-nds.de/startseite/kriminalitaet/statistik/polizeiliche-kriminalstatistik-2024-117999.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  239. Polizeipräsidium Mittelfranken (2025). Sicherheitsbericht 2024 [Safety report 2024]. https://www.polizei.bayern.de/mam/pp-mittelfranken/sonstige/250324_ppmfr_sicherheitsbericht-2024.pdf Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  240. Polizei Sachsen (2025). Polizeiliche Kriminalstatistik 2024 [Police crime statistics 2024]. https://www.polizei.sachsen.de/de/MI_2025_113172.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  241. Rafiee, A., Spooren, W., & Sanders, J. (2021). Framing similar issues differently: A cross-cultural discourse analysis of news images. Social Semiotics, 33(3), 515–538. https://doi.org/10.1080/10350330.2021.1900719 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  242. Rahlf, L. (2024). Beyond healthy skepticism: Exploring German news media framing of terrorism-affiliated women returnees. Studies in Conflict & Terrorism, 47(10), 1200–1229. https://doi.org/10.1080/1057610X.2021.2017395 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  243. Reinemann, C., & Baugut, P. (2014). Alter Streit unter neuen Bedingungen. Einflüsse politischer Einstellungen von Journalisten auf ihre Arbeit [Old conflict under new conditions: The influence of journalists’ political attitudes on their work]. Zeitschrift Für Politik, 61(4), 480–505. http://www.jstor.org/stable/24229238 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  244. Rössler, P. (2017). Inhaltsanalyse [Content analysis]. UVK. https://doi.org/10.36198/ 9783838547060 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  245. Ryan, H., & Tonkiss, K. (2023). Loners, criminals, mothers: The gendered misrecognition of refugees in the British tabloid news media. Sociological Research Online, 28(4), 995–1013. https://doi.org/10.1177/13607804221100555 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  246. Sächsische Staatskanzlei (2025, April 30). Innenminister zum Staatsschutz-Einsatz in Chemnitz [Interior minister on the state security operation in Chemnitz]. https://medienservice.sachsen.de/medien/news/1086745 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  247. Schröder, J. (2024, April 29). Die Verkaufszahlen der 122 größten Regionalzeitungen [Sales figures for the 122 largest regional newspapers]. https://meedia.de/news/beitrag/2911-die- verkaufszahlen-der-122-groessten-regionalzeitungen.html Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  248. Slakoff, D. C. (2020). The representation of women and girls of color in United States crime news. Sociology Compass, 14(1). https://doi.org/10.1111/soc4.12741 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  249. Slakoff, D. C., & Brennan, P. K. (2019). The differential representation of Latina and black female victims in front-page news stories: A qualitative document analysis. Feminist Criminology, 14(4), 488–516. https://doi.org/10.1177/1557085117747031 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  250. Threadcraft, S. (2017). North American necropolitics and gender: On #BlackLivesMatter and black femicide. South Atlantic Quarterly, 116(3), 553–579. https://doi.org/10.1215/00382876-3961483 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  251. Trebbe, J., & Schoenhagen, P. (2011). Ethnic minorities in the mass media: How migrants perceive their representation in Swiss public television. Journal of International Migration & Integration, 12, 411–428. https://doi.org/10.1007/s12134-011-0175-7 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  252. Wiesner, C. (2022). Doing qualitative and interpretative research: Reflecting principles and principled challenges. Political Research Exchange, 4(1). https://doi.org/10.1080/2474736X.2022.2127372 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  253. Yates, S. (2020). Gender, context and constraint: Framing family violence in Victoria. Women’s Studies International Forum, 78. https://doi.org/10.1016/j.wsif.2019.102321 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  254.   Open Google Scholar DOI: 10.5771/2192-4007-2026-2-009
  255. Anspach, N. M. (2017). The new personal influence: How our Facebook friends influence the news we read. Political Communication, 34(4), 590–606. https://doi.org/10.1080/10584609.2017.1316329 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  256. Appelman, A., & Sundar, S. S. (2016). Measuring message credibility: Construction and validation of an exclusive scale. Journalism & Mass Communication Quarterly, 93(1), 59–79. https://doi.org/10.1177/1077699015606057 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  257. Aronson, E., Wilson, T. D., & Sommers, S. R. (2021). Social psychology (10. ed., Global ed.). Pearson. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  258. Bakshy, E., Eckles, D., Yan, R., & Rosenn, I. (2012). Social influence in social advertising: Evidence from field experiments. Proceedings of the 13th ACM Conference on Electronic Commerce, 146–161. https://doi.org/10.1145/2229012.2229027 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  259. Bakshy, E., Messing, S., & Adamic, L. A. (2015). Exposure to ideologically diverse news and opinion on Facebook. Science, 348(6239), 1130–1132. https://doi.org/10.1126/science.aaa1160 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  260. Beam, M. A. (2014). Automating the news: How personalized news recommender system design choices impact news reception. Communication Research, 41(8), 1019–1041. https://doi.org/10.1177/0093650213497979 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  261. Boczkowski, P. J., Mitchelstein, E., & Matassi, M. (2018). “News comes across when I’m in a moment of leisure”: Understanding the practices of incidental news consumption on social media. New Media & Society, 20(10), 3523–3539. https://doi.org/10.1177/1461444817750396 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  262. Brewer, M. B. (1979). In-group bias in the minimal intergroup situation: A cognitive–motivational analysis. Psychological Bulletin, 86(2), 307–324. https://doi.org/10.1037/0033-2909.86.2.307 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  263. Bruns, A. (2019). Are filter bubbles real? Polity Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  264. Cakanlar, A., & White, K. (2023). A systematic review on political ideology and persuasion. Psychology & Marketing, 40(12), 2526–2538. https://doi.org/10.1002/mar.21894 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  265. Carr, C. T. (2017). Social media and intergroup communication. In Oxford Research Encyclopedias: Communication. https://doi.org/10.1093/acrefore/9780190228613.013.460 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  266. Chaiken, S. (1980). Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39(5), 752–766. https://doi.org/10.1037/0022-3514.39.5.752 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  267. Chartrand, T. L., & Bargh, J. A. (1999). The chameleon effect: The perception–behavior link and social interaction. Journal of Personality and Social Psychology, 76(6), 893–910. https://doi.org/10.1037/0022-3514.76.6.893 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  268. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621. https://doi.org/10.1146/annurev.psych.55.090902.142015 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  269. Dahlgren, P. M., Shehata, A., & Strömbäck, J. (2019). Reinforcing spirals at work? Mutual influences between selective news exposure and ideological leaning. European Journal of Communication, 34(2), 159–174. https://doi.org/10.1177/0267323119830056 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  270. de Benedictis-Kessner, J., Baum, M. A., Berinsky, A. J., & Yamamoto, T. (2019). Persuading the enemy: Estimating the persuasive effects of partisan media with the preference–incorporating choice and assignment design. American Political Science Review, 113(4), 902–916. https://doi.org/10.1017/S0003055419000418 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  271. Dvir-Gvirsman, S. (2019). I like what I see: Studying the influence of popularity cues on attention allocation and news selection. Information, Communication & Society, 22(2), 286–305. https://doi.org/10.1080/1369118X.2017.1379550 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  272. Fawzi, N., Steindl, N., Obermaier, M., Prochazka, F., Arlt, D., Blöbaum, B., Dohle, M., Engelke, K. M., Hanitzsch, T., Jackob, N., Jakobs, I., Klawier, T., Post, S., Reinemann, C., Schweiger, W., & Ziegele, M. (2021). Concepts, causes and consequences of trust in news media – a literature review and framework. Annals of the International Communication Association, 45(2), 154–174. https://doi.org/10.1080/23808985.2021.1960181 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  273. Fielding, K. S., Hornsey, M. J., Thai, H. A., & Toh, L. L. (2020). Using ingroup messengers and ingroup values to promote climate change policy. Climatic Change, 158(2), 181–199. https://doi.org/10.1007/s10584-019-02561-z Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  274. Flaxman, S., Goel, S., & Rao, J. M. (2016). Filter bubbles, echo chambers, and online news consumption. Public Opinion Quarterly, 80(S1), 298–320. https://doi.org/10.1093/poq/nfw006 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  275. Gigerenzer, G., Todd, P. M., & The ABC Research Group. (1999). Simple heuristics that make us smart. Oxford University Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  276. Gil de Zúñiga, H., Weeks, B., & Ardèvol-Abreu, A. (2017). Effects of the news-finds-me perception in communication: Social media use implications for news seeking and learning about politics. Journal of Computer-Mediated Communication, 22(3), 105–123. https://doi.org/10.1111/jcc4.12185 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  277. Haas, A., & Unkel, J. (2015). Glaubwürdigkeit und Selektion von Suchergebnissen: Der Einfluss von Platzierung, Reputation, Neutralität und sozialen Empfehlungen bei der Nutzung von Suchmaschinen [Credibility and selection of search results: The influence of placement, reputation, neutrality and social recommendations in search engine use]. Medien & Kommunikationswissenschaft, 63(3), 363–382. https://doi.org/10.5771/1615-634X-2015-3-363 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  278. Hartmann, D., Wang, S. M., Pohlmann, L., & Berendt, B. (2025). A systematic review of echo chamber research: Comparative analysis of conceptualizations, operationalizations, and varying outcomes. Journal of Computational Social Science, 8(2). https://doi.org/10.1007/s42001-025-00381-z Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  279. Hovland, C. I., & Weiss, W. (1951). The influence of source credibility on communication effectiveness. Public Opinion Quarterly, 15(4), 635–650. https://doi.org/10.1086/266350 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  280. Isenberg, D. J. (1986). Group polarization: A critical review and meta-analysis. Journal of Personality and Social Psychology, 50(6), 1141–1151. https://doi.org/10.1037/0022-3514.50.6.1141 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  281. Iyengar, S., & Hahn, K. S. (2009). Red media, blue media: Evidence of ideological selectivity in media use. Journal of Communication, 59(1), 19–39. https://doi.org/10.1111/j.1460-2466.2008.01402.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  282. Johnson, B. T., & Eagly, A. H. (1989). Effects of involvement on persuasion: A meta-analysis. Psychological Bulletin, 106(2), 290–314. https://doi.org/10.1037/0033-2909.106.2.290 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  283. Kahan, D. M. (2013). Ideology, motivated reasoning, and cognitive reflection. Judgment and Decision Making, 8(4), 407–424. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  284. Kaiser, J., Keller, T. R., & Kleinen-von Königslöw, K. (2018). Incidental news exposure on Facebook as a social experience: The influence of recommender and media cues on news selection. Communication Research, 48(1), 77–99. https://doi.org/10.1177/ 0093650218803529 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  285. Karnowski, V., Kümpel, A. S., Leonhard, L., & Leiner, D. J. (2017). From incidental news exposure to news engagement: How perceptions of the news post and news usage patterns influence engagement with news articles encountered on Facebook. Computers in Human Behavior, 76, 42–50. https://doi.org/10.1016/j.chb.2017.06.041 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  286. Keib, K., Wojdynski, B. W., Espina, C., Malson, J., Jefferson, B., & Lee, Y.-I. (2022). Living at the speed of mobile: How users evaluate social media news posts on smartphones. Communication Research, 49(7), 1016–1032. https://doi.org/10.1177/00936502211018542 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  287. Knobloch-Westerwick, S. (2008). Information seeking. In W. Donsbach (Ed.), The international encyclopedia of communication (pp. 2264–2268). Wiley-Blackwell. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  288. Knobloch-Westerwick, S., & Hastall, M. R. (2010). Please your self: Social identity effects on selective exposure to news about in- and out-groups. Journal of Communication, 60(3), 515–535. https://doi.org/10.1111/j.1460-2466.2010.01495.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  289. Knobloch-Westerwick, S., Johnson, B. K., & Westerwick, A. (2015). Confirmation bias in online searches: Impacts of selective exposure before an election on political attitude strength and shifts. Journal of Computer-Mediated Communication, 20(2), 171–187. https://doi.org/10.1111/jcc4.12105 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  290. Knobloch-Westerwick, S., Mothes, C., Johnson, B. K., Westerwick, A., & Donsbach, W. (2015). Political information searching in Germany and the United States: Confirmation bias, source credibility, and attitude impacts. Journal of Communication, 65(3), 489–511. https://doi.org/10.1111/jcom.12154 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  291. Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: A systematic review. Annals of the International Communication Association, 45(3), 188–206. https://doi.org/10.1080/23808985.2021.1976070 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  292. Kümpel, A. S. (2019). The issue takes it all? Incidental news exposure and news engagement on Facebook. Journal of Communication, 69(4), 373–395. https://doi.org/10.1093/joc/jqz019 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  293. Kümpel, A. S. (2021). Social media information environments and their implications for the uses and effects of news: The PINGS framework. Communication Theory, 32(2), 223–242. https://doi.org/10.1093/ct/qtab012 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  294. Leininger, A., Grünewald, F., & Buntfuß, N. (2023). Ideological and affective polarization in multiparty systems. OSF Preprints. https://doi.org/10.31235/osf.io/mz6rs Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  295. Lin, L. C., Qu, Y., & Telzer, E. H. (2018). Intergroup social influence on emotion processing in the brain. Proceedings of the National Academy of Sciences, 115(42), 10630–10635. https://doi.org/10.1073/pnas.1802111115 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  296. Luo, M., Hancock, J. T., & Markowitz, D. M. (2020). Credibility perceptions and detection accuracy of fake news headlines on social media: Effects of truth-bias and endorsement cues. Communication Research, 49(2), 171–195. https://doi.org/10.1177/0093650220921321 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  297. Mackie, D. M., Gastardo-Conaco, M. C., & Skelly, J. J. (1992). Knowledge of the advocated position and the processing of in-group and out-group persuasive messages. Personality and Social Psychology Bulletin, 18(2), 145–151. https://doi.org/10.1177/0146167292182005 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  298. McGarty, C., Haslam, S. A., Hutchinson, K. J., & Turner, J. C. (1994). The effects of salient group memberships on persuasion. Small Group Research, 25(2), 267–293. https://doi.org/10.1177/1046496494252007 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  299. Meijer, I. C., & Kormelink, T. G. (2014). Checking, sharing, clicking and linking: Changing patterns of news use between 2004 and 2014. Digital Journalism, 3(5), 664–679. https://doi.org/10.1080/21670811.2014.937149 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  300. Messing, S., & Westwood, S. J. (2014). Selective exposure in the age of social media: Endorsements trump partisan source affiliation when selecting news online. Communication Research, 41(8), 1042–1063. https://doi.org/10.1177/0093650212466406 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  301. Metzger, M. J., & Flanagin, A. J. (2013). Credibility and trust of information in online environments: The use of cognitive heuristics. Journal of Pragmatics, 59, 210–220. https://doi.org/10.1016/j.pragma.2013.07.012 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  302. Möller, J. (2021). Filter bubbles and digital echo chambers. In H. Tumber & S. Waisbord (Eds.), The Routledge companion to media disinformation and populism (pp. 92–100). Routledge. https://doi.org/10.4324/9781003004431-10 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  303. Molyneux, L. (2018). Mobile news consumption. Digital Journalism, 6(5), 634–650. https://doi.org/10.1080/21670811.2017.1334567 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  304. Mullen, B., Brown, R., & Smith, C. (1992). Ingroup bias as a function of salience, relevance, and status: An integration. European Journal of Social Psychology, 22(2), 103–122. https://doi.org/10.1002/ejsp.2420220202 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  305. Nelson, J. L., & Webster, J. G. (2017). The myth of partisan selective exposure: A portrait of the online political news audience. Social Media + Society, 3(3). https://doi.org/10.1177/2056305117729314 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  306. Newman, N., Fletcher, R., Schulz, A., Andi, S., Robertson, C. T., & Nielsen, R. K. (2021). Reuters Institute Digital News Report 2021. Reuters Institute for the Study of Journalism. https://reutersinstitute.politics.ox.ac.uk/digital-news-report/2021 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  307. Noelle-Neumann, E. (1993). The spiral of silence: Public opinion – Our social skin. University of Chicago Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  308. Ohme, J., & Mothes, C. (2020). What affects first- and second-level selective exposure to journalistic news? A social media online experiment. Journalism Studies, 21(9), 1220–1242. https://doi.org/10.1080/1461670X.2020.1735490 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  309. Ohme, J., & Mothes, C. (2025). News snacking and political learning: Changing opportunity structures of digital platform news use and political knowledge. Journal of Information Technology & Politics, 22(1), 1–15. https://doi.org/10.1080/19331681.2023.2193579 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  310. Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 19, pp. 123–205). Academic Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  311. Phillips, J. (2022). Affective polarization: Over time, through the generations, and during the lifespan. Political Behavior, 44(3), 1483–1508. https://doi.org/10.1007/s11109-022-09784-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  312. Rivera, L. M., Vu, H. A., & Backstrom, V. L. (2024). Self-esteem, ingroup favoritism, and outgroup evaluations: A meta-analysis. Group Processes & Intergroup Relations, 27(7), 1569–1588. https://doi.org/10.1177/13684302231210496 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  313. Ross, A. R., Chadwick, A., & Vaccari, C. (2021). Digital media and the proliferation of public opinion cues online: Biases and vulnerabilities in the new attention economy. In The Routledge companion to political journalism (pp. 241–251). Routledge. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  314. Sar, S., & Rodriguez, L. (2017). Copy test and starch test. In J. Matthes (Ed.), The international encyclopedia of communication research methods (pp. 1–6). Wiley. https://doi.org/10.1002/9781118901731.iecrm0047 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  315. Schweiger, W. (2025). Online-Informationen: Individuelle und gesellschaftliche Effekte [Online information: Individual and social effects]. In W. Schweiger, K. Beck, & V. Karnowski (Eds.), Handbuch Online-Kommunikation (pp. 1–19). Springer. https://doi.org/10.1007/978-3-658-18017-1_41-1 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  316. Sia, C.-L., Tan, B. C. Y., & Wei, K.-K. (2002). Group polarization and computer-mediated communication: Effects of communication cues, social presence, and anonymity. Information Systems Research, 13(1), 70–90. https://doi.org/10.1287/isre.13.1.70.92 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  317. Spears, R. (2021). Social influence and group identity. Annual Review of Psychology, 72, 367–390. https://doi.org/10.1146/annurev-psych-070620-111818 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  318. Spears, R., & Lea, M. (1994). Panacea or panopticon? The hidden power in computer-mediated communication. Communication Research, 21(4), 427–459. https://doi.org/10.1177/009365094021004003 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  319. Strömbäck, J., Wikforss, Å., Glüer, K., Lindholm, T., & Oscarsson, H. (2022). Knowledge resistance in high-choice information environments. Routledge. https://doi.org/10.4324/9781003111474 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  320. Sude, D., & Knobloch-Westerwick, S. (2022). Selective exposure and attention to attitude-consistent and attitude-discrepant information: Reviewing the evidence. In J. Strömbäck, Å. Wikforss, K. Glüer, T. Lindholm, & H. Oscarsson (Eds.), Knowledge resistance in high-choice information environments (pp. 88–105). Routledge. https://doi.org/10.4324/9781003111474-5 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  321. Sülflow, M., Schäfer, S., & Winter, S. (2019). Selective attention in the news feed: An eye-tracking study on the perception and selection of political news posts on Facebook. New Media & Society, 21(1), 168–190. https://doi.org/10.1177/1461444818791520 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  322. Sundar, S. S., & Nass, C. (2001). Conceptualizing sources in online news. Journal of Communication, 51(1), 52–72. https://doi.org/10.1111/j.1460-2466.2001.tb02872.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  323. Tajfel, H. (1978). Differentiation between social groups: Studies in the social psychology of intergroup relations. Academic Press. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  324. Turcotte, J., York, C., Irving, J., Scholl, R. M., & Pingree, R. J. (2015). News recommendations from social media opinion leaders: Effects on media trust and information seeking. Journal of Computer-Mediated Communication, 20(5), 520–535. https://doi.org/10.1111/jcc4.12127 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  325. Walther, E., Bless, H., Strack, F., Rackstraw, P., Wagner, D., & Werth, L. (2002). Conformity effects in memory as a function of group size, dissenters and uncertainty. Applied Cognitive Psychology, 16(7), 793–810. https://doi.org/10.1002/acp.828 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  326. Wei, Z., Ding, Y., Liu, X., & Dai, S. (2023). In-group and out-group social influence on punishment in unfair situations. Current Psychology, 42(21), 18396–18404. https://doi.org/10.1007/s12144-022-03027-9 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  327. Winter, S., Metzger, M. J., & Flanagin, A. J. (2016). Selective use of news cues: A multiple-motive perspective on information selection in social media environments. Journal of Communication, 66(4), 669–693. https://doi.org/10.1111/jcom.12241 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  328. Xu, Q. (2013). Social recommendation, source credibility, and recency: Effects of news cues in a social bookmarking website. Journalism & Mass Communication Quarterly, 90(4), 757–775. https://doi.org/10.1177/1077699013503158 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  329. Yardi, S., & Boyd, D. (2010). Dynamic debates: An analysis of group polarization over time on Twitter. Bulletin of Science, Technology & Society, 30(5), 316–327. https://doi.org/10.1177/0270467610380011 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  330. Zerback, T., & Fawzi, N. (2016). Can online exemplars trigger a spiral of silence? Examining the effects of exemplar opinions on perceptions of public opinion and speaking out. New Media & Society, 19(7), 1034–1051. https://doi.org/10.1177/1461444815625942 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  331.   Open Google Scholar DOI: 10.5771/2192-4007-2026-2-008
  332. Abramson, P. R., & Aldrich, J. H. (1982). The decline of electoral participation in America. American Political Science Review, 76(3), 502–521. https://econpapers.repec.org/article/cupapsrev/v_3a76_3ay_3a1982_3ai_3a03_3ap_3a502-521_5f18.htm Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  333. Aertsens, J., Mondelaers, K., Verbeke, W., Buysse, J., & van Huylenbroeck, G. (2011). The influence of subjective and objective knowledge on attitude, motivations and consumption of organic food. British Food Journal, 113(11), 1353–1378. https://doi.org/10.1108/00070701111179988 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  334. Andersen, K., Bjarnøe, C., Albæk, E., & Vreese, C. H. de (2016). How news type matters. Journal of Media Psychology, 28(3), 111–122. https://doi.org/10.1027/1864-1105/a000201 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  335. Annis, L. F. (1983). The processes and effects of peer tutoring. Human Learning: Journal of Practical Research & Applications, 2(1), 39–47. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  336. Bargh, J. A., & Schul, Y. (1980). On the cognitive benefits of teaching. Journal of Educational Psychology, 72(5), 593–604. https://doi.org/10.1037/0022-0663.72.5.593 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  337. Carr, C. T., & Foreman, A. C. (2016). Identity shift III: Effects of publicness of feedback and relational closeness in computer-mediated communication. Media Psychology, 19(2), 334–358. https://doi.org/10.1080/15213269.2015.1049276 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  338. Carr, C. T., & Hayes, R. A. (2019). Identity shift effects of self-presentation and confirmatory and disconfirmatory feedback on self-perceptions of brand identification. Media Psychology, 22(3), 418–444. https://doi.org/10.1080/15213269.2017.1396228 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  339. Carr, C. T., Kim, Y., Valov, J. J., Rosenbaum, J. E., Johnson, B. K., Hancock, J. T., & Gonzales, A. L. (2021). An explication of identity shift theory. Journal of Media Psychology, 33(4), 202–214. https://doi.org/10.1027/1864-1105/a000314 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  340. Cho, J., Ahmed, S., Keum, H., Choi, Y. J., & Lee, J. H. (2018). Influencing myself: Self-reinforcement through online political expression. Communication Research, 45(1), 83–111. https://doi.org/10.1177/0093650216644020 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  341. Choi, J., Lee, J. K., & Metzgar, E. T. (2017). Investigating effects of social media news sharing on the relationship between network heterogeneity and political participation. Computers in Human Behavior, 75, 25–31. https://doi.org/10.1016/j.chb.2017.05.003 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  342. Cialdini, R. B., & Goldstein, N. J. (2004). Social influence: Compliance and conformity. Annual Review of Psychology, 55, 591–621. https://doi.org/10.1146/annurev.psych.55.090902.142015 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  343. Cioffi, D., & Garner, R. (1996). On doing the decision: Effects of active versus passive choice on commitment and self-perception. Personality and Social Psychology Bulletin, 22(2), 133–147. https://doi.org/10.1177/0146167296222003 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  344. D’Angelo, J., & Moreno, M. (2019). Facebook-induced friend shift and identity shift: A longitudinal study of Facebook posting and collegiate drinking. Cyberpsychology, Behavior and Social Networking, 22(3), 186–191. https://doi.org/10.1089/cyber.2018.0246 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  345. Dreston, J. H., & Neubaum, G. (2023). How incidental and intentional news exposure in social media relate to political knowledge and voting intentions. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1250051 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  346. Eveland, W. P. (2004). The effect of political discussion in producing informed citizens: The roles of information, motivation, and elaboration. Political Communication, 21(2), 177–193. https://doi.org/10.1080/10584600490443877 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  347. Eveland, W. P., Shah, D. V., & Kwak, N. (2003). Assessing causality in the Cognitive Mediation Model. Communication Research, 30(4), 359–386. https://doi.org/10.1177/0093650203253369 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  348. Eveland, W. P., & Thomson, T. (2006). Is it talking, thinking, or both? A lagged dependent variable model of discussion effects on political knowledge. Journal of Communication, 56(3), 523–542. https://doi.org/10.1111/j.1460-2466.2006.00299.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  349. Flynn, L. R., & Goldsmith, R. E. (1999). A short, reliable measure of subjective knowledge. Journal of Business Research, 46(1), 57–66. https://doi.org/10.1016/S0148-2963(98)00057-5 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  350. Fiorella, L., & Mayer, R. E. (2013). The relative benefits of learning by teaching and teaching expectancy. Contemporary Educational Psychology, 38(4), 281–288. https://doi.org/10.1016/j.cedpsych.2013.06.001 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  351. Gil de Zúñiga, H., & Diehl, T. (2019). News finds me perception and democracy: Effects on political knowledge, political interest, and voting. New Media & Society, 21(6), 1253–1271. https://doi.org/10.1177/1461444818817548 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  352. Gil de Zúñiga, H., Molyneux, L., & Zheng, P. (2014). Social media, political expression, and political participation: Panel analysis of lagged and concurrent relationships. Journal of Communication, 64(4), 612–634. https://doi.org/10.1111/jcom.12103 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  353. Goffman, E. (1967). Interactional ritual: Essays on face-to-face behaviour. Penguin. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  354. Gonzales, A. L., & Hancock, J. T. (2008). Identity shift in computer-mediated environments. Media Psychology, 11(2), 167–185. https://doi.org/10.1080/15213260802023433 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  355. Kornfield, R., & Toma, C. L. (2020). When do online audiences amplify benefits of self-disclosure? The role of shared experience and anticipated interactivity. Journal of Broadcasting & Electronic Media, 64(2), 277–297. https://doi.org/10.1080/08838151.2020.1757366 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  356. Kwak, N., Williams, A. E., Wang, X., & Lee, H. (2005). Talking politics and engaging politics. Communication Research, 32(1), 87–111. https://doi.org/10.1177/0093650204271400 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  357. Lachner, A., Hoogerheide, V., van Gog, T., & Renkl, A. (2022). Learning-by-teaching without audience presence or interaction: When and why does it work? Educational Psychology Review, 34(2), 575–607. https://doi.org/10.1007/s10648-021-09643-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  358. Lane, D. S., Lee, S. S., Liang, F., Kim, D. H., Shen, L., Weeks, B. E., & Kwak, N. (2019). Social media expression and the political self. Journal of Communication, 69(1), 49–72. https://doi.org/10.1093/joc/jqy064 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  359. Leary, M. R., & Kowalski, R. M. (1990). Impression management: A literature review and two-component model. Psychological Bulletin, 107(1), 34–47. https://doi.org/10.1037/0033-2909.107.1.34 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  360. Lee, S., Diehl, T., & Valenzuela, S. (2022). Rethinking the virtuous circle hypothesis on social media: Subjective versus objective knowledge and political participation. Human Communication Research, 48(1), 57–87. https://doi.org/10.1093/hcr/hqab014 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  361. Litt, E. (2012). Knock, knock. Who’s there? The imagined audience. Journal of Broadcasting & Electronic Media, 56(3), 330–345. https://doi.org/10.1080/08838151.2012.705195 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  362. Litt, E., & Hargittai, E. (2016). The imagined audience on social network sites. Social Media + Society, 2(1). https://doi.org/10.1177/2056305116633482 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  363. Marquart, F., Goldberg, A. C., van Elsas, E. J., Brosius, A., & de Vreese, C. H. (2019). Knowing is not loving: media effects on knowledge about and attitudes toward the EU. Journal of European Integration, 41(5), 641–655. https://doi.org/10.1080/07036337.2018.1546302 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  364. McLeod, J. M., Daily, K., Guo, Z., Eveland, W. P., Bayer, J. A., Yang, S., & Wang, H. S. (1996). Community integration, local media use, and democratic processes. Communication Research, 23(2), 179–209. https://doi.org/10.1177/009365096023002002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  365. McLeod, J. M., Scheufele, D. A., Moy, P., Horowitz, E. M., Holbert, R. L., Zhang, W., Zubric, S., & Zubric, J. (1999). Understanding deliberation. Communication Research, 26(6), 743–774. https://doi.org/10.1177/009365099026006005 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  366. Müller, P., Schneiders, P., & Schäfer, S. (2016). Appetizer or main dish? Explaining the use of Facebook news posts as a substitute for other news sources. Computers in Human Behavior, 65, 431–441. https://doi.org/10.1016/j.chb.2016.09.003 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  367. Mullen, B., Atkins, J. L., Champion, D. S., Edwards, C., Hardy, D., Story, J. E., & Vanderklok, M. (1985). The false consensus effect: A meta-analysis of 115 hypothesis tests. Journal of Experimental Social Psychology, 21(3), 262–283. https://doi.org/10.1016/0022-1031(85)90020-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  368. Nabi, R. L., Huskey, R., Nicholls, S. B., Keblusek, L., & Reed, M. (2019). When audiences become advocates: Self-induced behavior change through health message posting in social media. Computers in Human Behavior, 99, 260–267. https://doi.org/10.1016/j.chb.2019.05.030 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  369. Nanz, A., & Matthes, J. (2022). Seeing political information online incidentally. Effects of first- and second-level incidental exposure on democratic outcomes. Computers in Human Behavior, 133. https://doi.org/10.1016/j.chb.2022.107285 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  370. Nekmat, E. (2012). Message expression effects in online social communication. Journal of Broadcasting & Electronic Media, 56(2), 203–224. https://doi.org/10.1080/08838151.2012.678513 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  371. Neubaum, G., & Krämer, N. C. (2018). What do we fear? Expected sanctions for expressing minority opinions in offline and online communication. Communication Research, 45(2), 139–164. https://doi.org/10.1177/0093650215623837 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  372. Neubaum, G., & Lane, D. S. (2023). Nevertheless, it persists: Political self-effects in the context of persistent social media. Journal of Media Psychology, 35(6), 375–386. https://doi.org/10.1027/1864-1105/a000372 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  373. Oeldorf-Hirsch, A. (2018). The role of engagement in learning from active and incidental news exposure on social media. Mass Communication and Society, 21(2), 225–247. https://doi.org/10.1080/15205436.2017.1384022 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  374. Otto, L., & Bacherle, P. (2011). Politisches Interesse Kurzskala (PIKS) – Entwicklung und Validierung [Political interest short scale – development and validation]. Politische Psychology, 1(1), 19–35. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  375. Park, C. Y. (2001). News media exposure and self-perceived knowledge: The illusion of knowing. International Journal of Public Opinion Research, 13(4), 419–425. https://doi.org/10.1093/ijpor/13.4.419 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  376. Paulhus, D. L. (1991). Measurement and control of response bias. In J. P. Robinson, P. R. Shaver, & L. S. Wrightsman (Eds.), Measures of personality and social psychological attitudes (pp. 17–59). Academic Press. https://doi.org/10.1016/B978-0-12-590241-0.50006-X Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  377. Petty, R. E., & Cacioppo, J. T. (1986). Communication and persuasion: Central and peripheral routes to attitude change. Springer series in social psychology. Springer. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  378. Pingree, R. J. (2007). How messages affect their senders: A more general model of message effects and implications for deliberation. Communication Theory, 17(4), 439–461. https://doi.org/10.1111/j.1468-2885.2007.00306.x Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  379. Prochazka, F., Cantzler, J., Göthert, H., Hartung, S., Konermann, S., Lotz, J., Neureither, E., & Nittel, R. (2025). Self-effects of online commenting in different opinion environments. Communication Research Reports, 1–13. https://doi.org/10.1080/08824096.2025.2462594 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  380. Prior, M. (2010). You’ve either got it or you don’t? The stability of political interest over the life cycle. The Journal of Politics, 72(3), 747–766. https://doi.org/10.1017/S0022381610000149 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  381. R Core Team. (2021). R: A language and environment for statistical computing. R foundation for statistical computing, Vienna. https://www.R-project.org/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  382. Raju, P. S., Lonial, S. C., & Glynn Mangold, W. (1995). Differential effects of subjective knowledge, objective knowledge, and usage experience on decision making: An exploratory investigation. Journal of Consumer Psychology, 4(2), 153–180. https://doi.org/10.1207/s15327663jcp0402_04 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  383. Rios, K., Goldberg, M. H., & Totton, R. R. (2018). An informational influence perspective on (non) conformity: Perceived knowledgeability increases expression of minority opinions. Communication Research, 45(2), 241–260. https://doi.org/10.1177/0093650217699935 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  384. Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of Statistical Software, 48(2), 1–36. http://www.jstatsoft.org/v48/i02/ Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  385. Schäfer, S. (2020). Illusion of knowledge through Facebook news? Effects of snack news in a news feed on perceived knowledge, attitude strength, and willingness for discussions. Computers in Human Behavior, 103, 1–12. https://doi.org/10.1016/j.chb.2019.08.031 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  386. Schlenker, B. R., Dlugolecki, D. W., & Doherty, K. (1994). The impact of self-presentations on self-appraisals and behavior: The power of public commitment. Personality and Social Psychology Bulletin, 20(1), 20–33. https://doi.org/10.1177/0146167294201002 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  387. Schoemann, A. M., Boulton, A. J., & Short, S. D. (2017). Determining power and sample size for simple and complex mediation models. Social Psychological and Personality Science, 8(4), 379–386. https://doi.org/10.1177/1948550617715068 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  388. Shah, D. V., Cho, J., Eveland, W. P., & Kwak, N. (2005). Information and expression in a digital age: Modeling internet effects on civic participation. Communication Research, 32(5), 531–565. https://doi.org/10.1177/0093650205279209 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  389. Stromback, J., Djerf-Pierre, M., & Shehata, A. (2013). The dynamics of political interest and news media consumption: A longitudinal perspective. International Journal of Public Opinion Research, 25(4), 414–435. https://doi.org/10.1093/ijpor/eds018 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  390. Sundar, S. S., Snyder, E. C., Liao, M., Yin, J., Wang, J., & Chi, G. (2024). Sharing without clicking on news in social media. Nature Human Behaviour, 9(1), 156–168. https://doi.org/10.1038/s41562-024-02067-4 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  391. Swann, W. (1983). Bringing social reality into harmony with the self. In J. Suls & A. G. Greenwald (Eds.), Social psychological perspectives on the self (Vol. 2, pp. 33–66). Lawrence Erlbaum Associates. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  392. Tetlock, P. E., Skitka, L., & Boettger, R. (1989). Social and cognitive strategies for coping with accountability: Conformity, complexity, and bolstering. Journal of Personality and Social Psychology, 57(4), 632–640. https://doi.org/10.1037/0022-3514.57.4.632 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  393. Tice, D. M. (1992). Self-concept change and self-presentation: The looking glass self is also a magnifying glass. Journal of Personality and Social Psychology, 63(3), 435–451. https://doi.org/10.1037//0022-3514.63.3.435 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  394. Valkenburg, P. M. (2017). Understanding self-effects in social media. Human Communication Research, 43(4), 477–490. https://doi.org/10.1111/hcre.12113 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  395. van Oosten, J. M. F., Vries, D. A. de, & Peter, J. (2018). The importance of adolescents’ sexually outgoing self-concept: Differential roles of self- and other-generated sexy self-presentations in social media. Cyberpsychology, Behavior and Social Networking, 21(1), 5–10. https://doi.org/10.1089/cyber.2016.0671 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  396. Walther, J. B., Liang, Y. J., DeAndrea, D. C., Tong, S. T., Carr, C. T., Spottswood, E. L., & Amichai-Hamburger, Y. (2011). The effect of feedback on identity shift in computer-mediated communication. Media Psychology, 14(1), 1–26. https://doi.org/10.1080/15213269.2010.547832 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  397. Wang, J., & Sundar, S. S. (2022). Liking versus commenting on online news: Effects of expression affordances on political attitudes. Journal of Computer-Mediated Communication, 27(6), 1-13. https://doi.org/10.1093/jcmc/zmac018 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  398. Ward, A. F., Zheng, J., & Broniarczyk, S. M. (2023). I share, therefore I know? Sharing online content ‐ even without reading it ‐ inflates subjective knowledge. Journal of Consumer Psychology, 33(3), 469–488. https://doi.org/10.1002/jcpy.1321 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  399. Weber, M., & Köhler, C. (2017). Illusions of knowledge. International Journal of Communication, 11, 2387–2410. Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010
  400. Winter, S., Vos, A. L., Remmelswaal, P., & Neijens, P. (2024). How social are self-effects? The impact of feedback on the internalization of expressed opinions in online communication. Computers in Human Behavior Reports, 13. https://doi.org/10.1016/j.chbr.2023.100365 Open Google Scholar DOI: 10.5771/2192-4007-2026-2-010

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