{"id":7119,"date":"2025-11-24T11:00:41","date_gmt":"2025-11-24T10:00:41","guid":{"rendered":"https:\/\/leibniz-hbi.de\/?post_type=hbi-publications&p=7119"},"modified":"2025-12-29T11:26:15","modified_gmt":"2025-12-29T10:26:15","slug":"algorithmic-competence-of-young-people-on-tiktok","status":"publish","type":"hbi-publications","link":"https:\/\/leibniz-hbi.de\/en\/hbi-publications\/algorithmic-competence-of-young-people-on-tiktok\/","title":{"rendered":"Algorithmic Competence of Young People on TikTok"},"content":{"rendered":"

A new qualitative #UseTheNews<\/a> study by the Leibniz Institute for Media Research examined what teenagers and young adults know about how the algorithmic recommendation system (ARS) on TikTok works, how they interact with it, and the emotions involved. The study uses contemporary approaches to teaching news, information and media literacy to help prepare young people to resist the influence of algorithms.<\/p>\n

The study involved six focus groups (n = 31) of young people aged between 16 and 24 in three major German cities, as well as 12 follow-up individual interviews.<\/p>\n

\"CoverAvailable for Download (pdf)<\/strong>: Alatassi, Leonie; H\u00f6lig, Sascha; Kessling, Philipp \u00a0(2025): Zwischen Wertsch\u00e4tzung und Widerstand: Algorithmische Kompetenz junger Menschen am Beispiel der Kurzvideoplattform<\/span> TikTok [Between Appreciation and Resistance: Algorithmic Competence of Young People Using the Example of the Short Video Platform TikTok]. Hamburg: Verlag Hans-Bredow-Institut, November 2025 (Working Papers of the Hans-Bredow-Institut<\/a> | Project Results No. 79), https:\/\/doi.org\/10.21241\/ssoar.106121<\/a><\/p>\n

Summary of the Findings<\/h2>\n
    \n
  • There is a high level of awareness of algorithmic recommendations on TikTok as a lived experience (\u201cknowing\u201d) that results with personal use of the platform. There are age-related differences in knowledge of influencing factors and, overall, limited knowledge of data collection and processing, accompanied by low levels of concern and reflection about the disclosure of personal data.<\/li>\n
  • Search, video, profile and social interaction features are embedded in everyday platform use and largely take place unconsciously, without any explicit intent to control. Participants can act within the structures provided by the platform and set goals, but they perceive the technical limitations as difficult to influence. They often lack the knowledge and motivation to actively change more in-depth settings relating to data protection, personalised search or profile settings.<\/li>\n
  • Emotions play a significant part in interactions with the For You Page (FYP). Participants experience positive feelings of appreciation when they perceive the algorithm as a personalised companion that recognises their individual preferences, inspires them and enhances their user experience. At the same time, negative emotions such as annoyance, discomfort or a loss of control arise, particularly when confronted with inappropriate content, perceived overcontrol by the algorithm or one’s own usage time. These feelings can lead to resistance in the form of active interactions or self-regulatory strategies (e.g. deleting the app), expressing a desire for autonomy.<\/li>\n
  • It is important to distinguish between passively coming across political content on TikTok (push: ‘I watch political videos that are recommended to me’) and actively seeking out information through curation practices such as liking videos, following profiles and viewing them, or using the search function (pull: ‘I use the platform to inform myself’). Generally, most participants find it convenient when news or political topics are displayed in the form of short videos on the FYP, as passively scanning this content gives them a sense of being ‘up to date’. Very few participants actively seek out political content by searching for topics, favouriting political videos, or viewing and following political profiles.<\/li>\n
  • Focusing on news and politics on TikTok contradicts the escapism and entertainment needs of many users. There is fundamental scepticism towards TikTok based on the platform’s \u201cuntrustworthy\u201d image, and the fear of \u201cfalse information\u201d, which leads to the perception that TikTok is not a \u201creputable\u201d source, but purely an entertainment platform.<\/li>\n
  • Keywords: algorithmic recommendation systems, algorithmic competence, interaction processes, short video platform TikTok, data donations, qualitative research<\/li>\n<\/ul>\n","protected":false},"featured_media":681,"template":"","tags":[322],"class_list":["post-7119","hbi-publications","type-hbi-publications","status-publish","has-post-thumbnail","hentry","tag-working-paper"],"acf":[],"yoast_head":"\nAlgorithmic Competence of Young People on TikTok - Leibniz Institut f\u00fcr Medienforschung | Leibniz Institute for Media Research<\/title>\n<meta name=\"description\" content=\"A new qualitative #UseTheNews study by the Leibniz Institute for Media Research examines what teenagers and young adults know about how TikTok's algorithmic recommendation system works.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/leibniz-hbi.de\/en\/hbi-publications\/algorithmic-competence-of-young-people-on-tiktok\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Algorithmic Competence of Young People on TikTok\" \/>\n<meta property=\"og:description\" content=\"A new qualitative #UseTheNews study by the Leibniz Institute for Media Research examines what teenagers and young adults know about how TikTok's algorithmic recommendation system works.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/leibniz-hbi.de\/en\/hbi-publications\/algorithmic-competence-of-young-people-on-tiktok\/\" \/>\n<meta property=\"og:site_name\" content=\"Leibniz Institut f\u00fcr Medienforschung | Leibniz Institute for Media Research\" \/>\n<meta property=\"article:modified_time\" content=\"2025-12-29T10:26:15+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/leibniz-hbi.de\/wp-content\/uploads\/2024\/02\/page_dummy_publikationen.jpg\" \/>\n\t<meta property=\"og:image:width\" content=\"1380\" \/>\n\t<meta property=\"og:image:height\" content=\"400\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/jpeg\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"4 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/leibniz-hbi.de\\\/en\\\/hbi-publications\\\/algorithmic-competence-of-young-people-on-tiktok\\\/\",\"url\":\"https:\\\/\\\/leibniz-hbi.de\\\/en\\\/hbi-publications\\\/algorithmic-competence-of-young-people-on-tiktok\\\/\",\"name\":\"Algorithmic Competence of Young People on TikTok - 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