Who informs Germans about the Russia-Ukraine War on YouTube?


  • Tim Glaesener Malmö University


YouTube, source diversity, search results, Russo-Ukrainian War, Germany, mainstream media, alternative media, participatory media


Even though YouTube is often considered to be a platform for user-generated content, mainstream media has been present on the platform for years. However, the extent to which mainstream media can dominate YouTube is unknown. This study addresses this knowledge gap by exploring the source diversity of German language search results about the Russia-Ukraine War and applying the concepts of mainstream media and alternative media. Two scraping audits collected the top 20 results for the search “Russland Ukraine” (meaning “Russia Ukraine” in German) over 21 consecutive days. The results revealed two major findings: first, most of search results came from YouTube channels of the mainstream media (409 out of 420 in the first audit; 410 out of 420 in the second audit). Second, on average, most of the 20 search results were new every day (12 in the first audit; 14 in the second audit). These results demonstrate that German media organizations related to the newspaper, television, radio, and magazine industries can extend their reach from their traditional media channels to YouTube—at least regarding German search results related to the Russia-Ukraine War during data collection.


Airoldi, M., Beraldo, D., & Gandini, A. (2016). Follow the algorithm: an exploratory investigation of music on YouTube. Poetics, 57, 1–13. https://doi.org/10.1016/j.poetic.2016.05.001

Anderson, C. W. (2016). Assembling publics, assembling routines, assembling values: Journalistic self-conception and the crisis in journalism. In Alexander, J. C.; Butler, E., & Luengo, M. (Eds.). The Crises of journalism reconsidered: Democratic culture, professional codes, digital future (153- 169). Cambridge University Press.

Andrejevic, M. (2009). Exploiting YouTube: the contradictions of user-generated labor. In P. Snickars & P. Vonderau (Eds.), The YouTube Reader. (pp. 406–423) National Library of Sweden.

Benson, R. (2013). Shaping immigration news: A French-American comparison. Cambridge University Press.

Bishop, S. (2019). Managing visibility on YouTube through algorithmic gossip. New Media & Society, 21(11–12), 2589–2606. https://doi.org/10.1177/1461444819854731

Blaikie, N., & Priest, J. (2019). Designing Social Research (3rd ed). Polity Press.

Burgess, J., & Green, J. (2009b). YouTube: Online Video and Participatory Culture. Polity Press.

Burgess, J., & Green, J. (2009a). The entrepreneurial vlogger: Participatory culture beyond the professional/amateur divide. In P. Snickars & P. Vonderau (Eds.), The YouTube Reader. (pp. 89–107) National Library of Sweden.

Dean, B. (2021, September 7). How Many People Use YouTube in 2022? [New Data]. Backlino. https://backlinko.com/youtube-users#youtube-statistics

Die Medienanstalten (2021a). Intermediäre und Meinungsbildung. https://www.die-medienanstalten.de/themen/forschung/intermediaere-und-meinungsbildung

Die Medienanstalten (2021b). Medienvielfaltsmonitor 2021-I: Anteile der Medienangebote und Medienkonzerne am Meinungsmarkt der Medien in Deutschland. https://www.die-medienanstalten.de/themen/forschung/medienvielfaltsmonitor

Die Medienanstalten (2022). Jahrbuch 21. https://www.die-medienanstalten.de/publikationen/jahrbuch/jahrbuch-2021

Dilevko, J. & Kalina, G. (1997). A New Approach to Collection Bias in Academic Libraries: The Extent of Corporate Control in Journal Holdings. Library & Information Science Research, 19(4), 359–85.

Elghul-Bebawi, S. (2009). The Relationship between Mainstream and Alternative Media: A Blurring of the Edges?. In J. Gordon (Ed.), Notions of Community: A Collection of Community Media Debates and Dilemmas (pp. 17–32). Peter Lang.

Gibbs, M., Meese J., Arnold, M., Nasnen, B., & Carter, M. (2015). #Funeral and Instagram: Death, social media, and platform vernacular. Information, Communication & Society, 18(3), 255–268. https://doi.org/10.1080/1369118X.2014.987152

Gillespie, T. (2017). Algorithmically recognizable: Santorum’s Google problem, and Google’s Santorum problem. Information, Communication & Society, 20(1), 63–90. https://doi.org/10.1080/1369118X.2016.1199721

Google. (2022, May 13). Google Trends. https://trends.google.de/trends/explore?date=2022-02-23%202022-05-13&geo=DE&gprop=youtube&q=Russland%20Ukraine%20Krieg,russland%20ukraine

Heuer, H., Hoch, H., Breiter, A., & Theocharis, Y. (2021). Auditing the Biases Enacted by YouTube for Political Topics in Germany. In Mensch und Computer 2021 (MuC '21) (pp. 456–468). Association for Computing Machinery. https://doi.org/10.1145/3473856.3473864

Holt, K, Figenschou, T. U., Frischlich, L. (2019). Key dimensions of alternative news media. Digital Journalism, 7(7), 860–869. https://doi.org/10.1080/21670811.2019.1625715

Jenkins, H. (2006). Convergence Culture: Where Old and New Media Collide. New York University Press.

Jenkins, H., Purushotma, R., Weigel, M., Clinton, K., & Robison, A. J. (2009). Confronting the Challenges of Participatory Culture: Media Education for the 21st Century. John D. and Catherine T. MacArthur Foundation https://www.macfound.org/media/article_pdfs/jenkins_white_paper.pdf

Kaiser, J., Rauchfleisch, A., & Córdova, Y. (2021). Fighting Zika With Honey: An Analysis of YouTube’s Video Recommendations on Brazilian YouTube. International Journal of Communication, 15, 1244–1262.

Kenix, L. J. (2011). Alternative and Mainstream Media: The Converging Spectrum. Bloomsbury.

Kim, J. (2012). The institutionalization of YouTube: From user-generated content to professionally generated content. Media, Culture & Society, 34(1), 53–67. https://doi.org/10.1177/0163443711427199

Krafft, T. D., Gamer, M., & Zweig, K. A. (2018). What did you see? Personalization, regionalization and the question of the filter bubble in Google's search engine. ArXiv, abs/1812.10943. https://doi.org/10.48550/arXiv.1812.10943

Ledwich, M.., & Zaitsev. A. (2020). Algorithmic extremism: Examining YouTube’s rabbit hole of radicalization. First Monday, 25(3). https://doi.org/10.5210/fm.v25i3.10419

Matamoros-Fernández, A., Gray, J., Bartolo, L., Burgess, J., & Suzor, N. (2021). What’s “Up Next”? Investigating Algorithmic Recommendations on YouTube Across Issues and Over Time. Media and Communication, 9(4), 234–249. https://doi.org/10.17645/mac.v9i4.4184

May, A. L. (2010). Who Tube? How YouTube’s News and Politics Space Is Going Mainstream. The International Journal of Press/Politics, 15(4), 499–511. https://doi.org/10.1177/1940161210382861

McQuail, D. (1992). Media performance: Mass communication and the public interest. Sage.

Mohr, M. J., & Ventresca, J. W. (2017). Archival Research Methods. In J. A. C. Baum (Ed.) The Blackwell Companion to Organizations (pp. 805-828) Wiley. https://doi.org/10.1002/9781405164061.ch35

Morreale, J. (2014). From homemade to store bought: Annoying Orange and the professionalization of YouTube. Journal of Consumer Culture, 14, 113–128. https://doi.org/10.1177/1469540513505608

Rauch, J. (2016). Are There Still Alternatives? Relationships Between Alternative Media and Mainstream Media in a Converged Environment. Sociology Compass, 10(9), 756–767.

Ribeiro, M. H., Ottoni, R., West, R., Almeida, V. A., & Meira, W. (2020). Auditing radicalization pathways on YouTube. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 131–141. https://doi.org/10.1145/3351095.3372879

Rieder, B. (2022). YouTube Data Tools. https://tools.digitalmethods.net/netvizz/youtube/

Rieder, B., & Hofmann, J. (2020). Towards platform observability. Internet Policy Review, 9(4). https:// doi.org/10.14763/2020.4.1535

Rieder, B., Matamoros-Fernández, A., & Coromina, Ò. (2018). From ranking algorithms to ‘ranking cultures’: Investigating the modulation of visibility in YouTube search results. Convergence, 24(1), 50–68. https://doi.org/10.1177/1354856517736982

Riff, D., Lacy, S., & Fico, F. (2013). Analyzing Media Messages: Using Quantitative Content Analysis in Research (3rd ed.). Routledge. https://doi.org/10.4324/9780203551691

Roth C., Mazieres, A., Menezes, T. (2020). Tubes and bubbles topological confinement of YouTube recommendations. PLoS ONE, 15(4), 1–17 https://doi.org/10.1371/journal.pone.0231703

Sandvig, C., Hamilton, K., Karahalios, K., & Langbort, C. (2014, May 22). Auditing Algorithms: Research Methods for Detecting Discrimination on Internet Platforms. [Paper presentation]. 64th Annual Meeting of the International Communication Association. Seattle, WA, USA.

Snickars, P., & Vonderau, P. (2009). Introduction. In P. Snickars & P. Vonderau (Eds.), The YouTube Reader. (pp. 9–21) National Library of Sweden.

The YouTube Team. (2019c, December 3). The Four Rs of Responsibility, Part 2: Raising authoritative content and reducing borderline content and harmful misinformation. YouTube Official Blog. https://blog.youtube/inside-youtube/the-four-rs-of-responsibility-raise-and-reduce/

Thurman, N. (2011). Making ‘the Daily Me’: Technology, Economics and Habit in the Mainstream Assimilation of Personalized News. Journalism, 12(4), 395–415.

Townsend, L., & Wallace, C. (2016). Social Media Research: A Guide to Ethics. University of Aberdeen.

Van Dijck, J. (2013). The Culture of Connectivity: A Critical History of Social Media. Oxford University Press.