Parameterization of manipulative media discourse: possibilities and problems of automatic diagnosis

Abstract

The issue of quantitative measurement and automatic processing is a significant problem in determining the markers of the manipulative potential of media texts, since linguistic indicators are the basis of machine parameterization. The purpose of the research is to analyse the possibilities of the main language parameters of the manipulativeness of media discourse, which can be identified using machine learning. To achieve the research goals, the following methods were used: system, content analysis, computer modelling, and comparative. The results of the article determined that such language indicators as use of the subjunctive mood of verbs, capital letters, high frequency of use of the ‘not’ particle, punctuation marks, questions, or exclamations of a rhetorical nature, use of quotation marks for the purpose of irony, double negative sentences, use of the word ‘no’, and verbal structures calling to action act as computer classification parameters. In order to cover the above purpose, PYTHON software was implemented that allowed texts to be analysed and visualized in algorithmic and lexical-vocabulary ways. In addition, it was determined that by integrating the PYTHON tool, it became possible to use language transformation markers that formed linguistic patterns in the analysed text. The list of parameters for diagnosing manipulative texts is non-exhaustive, which emphasizes the possibility of machine measurement of the manipulative component of mass media discourse.