Abstract
The development of artificial intelligence technologies significantly transforms the process of creating media-texts. The modern journalist must consider the mechanisms behind recommendation algorithms not only when choosing their subject but also when choosing means of expression within the text. This creates many problems - both creative and technical-technological ones. In this article, we attempt to analyse the recommendation algorithms of social networks (Vkontakte, Dzen, Twitter), video-hosting sites (YouTube, Tiktok) and major search engines, determine their influence on the creative process, outreach, and consumption of media-texts. Relying on the method of content-analysis as well as the historical-functional method, we highlight key issues that result from recommendation algorithms and suggest possible solutions.
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