This paper assesses the degree of news coverage by topic by applying structural topic modelling. The preliminary stage involves the computer-aided gathering and systematisation of information from the Lenta.ru online news portal, converting words into a single form, and cleaning the text data from stopwords. The method of structural thematic modelling (STM) was used in this study, which made it possible to identify the 25 most popular topics for publication on the news portal and to determine the frequency of occurrence of the words in the subject and their uniqueness. Correlation and regression analyses indicated the correlation of the topics under study and the change in the degree of coverage of the topics over time.