The paper considers the problem of topic modeling and evaluation of topic models, presented in marked up sets of text messages, based on the Word2vec word vector representation model. Clusters constructed as a result of the word vectors analysis can be used for various tasks, including diagnostics of the topic model presented in the marked up collection of text messages. For this purpose, it was proposed to calculate the intersection matrix between the dictionary clusters formed for the entire text corpus and the individual dictionaries of topic subsets in the corpus. The paper presents and discusses the results of a machine experiment with a collection of news messages of one of the regional online media. The results of the experiment demonstrated the feasibility of potential diagnostics for the existing system of topic categories in a collection of text messages and determining the possible directions of its reorganization.