The paper discusses the experiments on dynamic topic modeling of the corpus of Russian governmental posts from VKontakte social network. The study is aimed at detecting hidden topical relations and tracking the evolvement of main topics within the text collection. The experiments were conducted on ministerial posts from 15 communities, we give explanations on the resultant dynamic topic models, and establish links with the issues that were important at a specific period in the Russian government. The results justify the use of dynamic topic modeling as a means of social media analysis that can be applied to Russian corpora of Internet texts.