Nowadays the interests of linguists are aimed at analyzing text collections with the help of automatic procedures. They pay special attention to the texts on social networks as their language features differ from the features of fiction texts or scientific articles. The paper is dedicated to the creation of dynamic topic models of Lentach news posts on VK social network. We use a mixture of NLP libraries to identify the semantic shifts of main topical sets since the end of 2018. The corpus contains more than 26,000 posts on various topics. In contemporary Russian linguistic papers, the collection of Lentach posts is rarely analyzed in terms of NLP. The results show that the main topics that are widely discussed in this community cover sports events, health issues, and protests.