The rampant spread of manipulative texts purporting propaganda, disinformation or surveillance, requires the readers to take heed of the actual reasoning behind and the real purpose of the newspaper texts. The capability to recognize a malignant content asks for more and more concentration and background knowledge. A support offered by automated content analysis tools forms an important part of such protective approaches. In the presented text, we introduce a new approach to detecting a set of manipulative stylistic techniques in Czech newspaper texts by exploiting stylometric methods in conjunction with deep learning text classification. We show that the stylometric analysis with almost 20,000 features allows to improve the results for most of the techniques. The results are evaluated with a previously published Czech Propaganda dataset.