Abstract
<jats:p>In the context of digital transformation, algorithmic mediation of platforms increasingly determines users’ access to news content, but its impact on media trust in post-Soviet media systems, in particular in Kazakhstan, remains poorly understood. The aim of the work is to identify the level of algorithmic awareness of Internet users in Kazakhstan and to determine the nature of its relationship with trust in traditional media, social networks and the Telegram messenger. The main areas include theoretical analysis of algorithmic power and media plat-formization, as well as empirical measurement of cognitive and behavioral aspects of awareness. A brief description of the scientific and practical significance of the work. The scientific significance lies in the adaptation of Western concepts of algorithmic awareness to the Kazakh context. The practical significance lies in the possibility of using the findings in the development of educational programs for media literacy and policies to increase the transparency of algorithms. A brief description of the research methodology. The empirical basis is a quantitative online survey (n = 50) conducted in March 2026. A four-level model of algorithmic awareness (declarative knowl-edge, process understanding, reflexive awareness, behavioral response) and a scale of media trust using the Likert method were used. Main results and analysis, conclusions. Respondents demonstrate a high level of declarative aware-ness of algorithms (M = 3.99), but weak behavioral reflection. Trust in traditional media is low (M = 2.93), and in social networks it is even lower (M = 2.67). There is no statistically significant relationship between awareness and trust, which indicates the dominance of historical and institutional factors of distrust. The value of the conducted research. For the first time, the work empirically verifies the concept of algorithmic awareness in the Kazakh media space, revealing the gap between knowledge of algorithms and information hygiene practices. The practical significance of the results of the work. The results can be used in the development of modules on algorithmic literacy for schools and universities, as well as in the discussion of measures to increase the transparency of recommendation systems of digital platforms.</jats:p>