Determining the level of propaganda in opera librettos using data mining and machine learning

The article presents an adapted multifactorial model that can be used to determine the level of propaganda in librettos to world operas. This model was created using the linear convolution method, for which eight indicators were selected that are most effective in identifying elements of propaganda in the text, taking into account the subject area's peculiarities. Each of the selected indicators was calculated using statistical analysis, data mining, and machine learning methods. As a result of applying the proposed method, the value function is calculated for each libretto, based on which a conclusion is made as to whether it contains elements of propaganda or not.