DISCOURSE ANALYSIS OF POLITICAL JUDGMENTS IN THE CONTEXT OF DIGITALIZATION
DOI:
https://doi.org/10.21638/spbu23.2021.303Abstract
Discourse analysis of texts and speeches has been one of the most popular research methods since the second half of the XX century. Its emergence is associated with the works of postmodernists, such as Deleuze, J. Derrida, M. Foucault, E. Laclos, and S. Mouffe. The method is interesting because it allows us to take into account the context of expressed judgments and to uncover the implied meaning of statements. Despite the widespread use of this method, no unified methodology has been created. In foreign and Russian science, parallel trends and schools in the field of discourse analysis were formed, the most influential of which is discussed in this article. The emergence of social networks, digital platforms and applications has set a new trend in modifying and creating new variants of discourse analysis of texts and judgments, but already in a digital environment. Some of them, such as Y.G. Misnikov’s approach, can serve as an alternative to studying public opinion by means of a social survey. The purpose of this article is to analyze and systematize both traditional methods of discourse analysis of political judgments and new approaches using social networks, apps, websites, and digital platforms. In the course of the research, the methods of classification and systematization as well as, general scientific methods of analysis and synthesis were used. In the context of digitalization, five varieties of discourse analysis method were considered for text analysis in a digital environment: critical discourse analysis, corpus discourse analysis, mediated discourse analysis, multimodal discourse analysis, and discourse analysis using artificial intelligence. A thorough analysis of these methods allowed us to identify a gap in the analysis of political judgments on digital platforms of interaction between the government and the population, and to propose a variant of filling it on the basis of A. Kruglanski's parametric model.
Keywords:
discourse analysis, critical discourse analysis, social media, mobile applications, neural networks, political judgments
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