Malysheva O.P., Ryabchenko N.A. Networked Linguistic Data and Discourse Management: The 2020 US Presidential Election

DOI: https://doi.org/10.15688/jvolsu2.2022.3.4

Olga P. Malysheva

Candidate of Sciences (Philology), Associate Professor, Department of English Philology, Kuban State University

Stavropolskaya St, 149, 350040 Krasnodar, Russia

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https://orcid.org/0000-0001-8285-0508

Natalia A. Ryabchenko

Candidate of Sciences (Politics), Associate Professor, Department of Social Work, Psychology and Pedagogy of Higher Education, Kuban State University

Stavropolskaya St, 149, 350040 Krasnodar, Russia

This email address is being protected from spambots. You need JavaScript enabled to view it.

https://orcid.org/0000-0001-6980-2894

Abstract. The article introduces the methodology used for analyzing networked linguistic data, regarded as a basis of global online discursive fields. The authors scrutinized the discursive fields, which emerged during 2020 US Presidential Election.The research methodology, which combines natural science methods (mathematical analysis, graph theory, network analysis and relational analysis) and modern methods of linguistic research (complex linguo-discursive analysis, and methods of network linguistics), makes it possible to analyze discursive fields as social graphs, identify narratives and discourses that form the basis of the modern global communication space, and their potential for manipulating. The empirical base of the study is comprised of bulks of networked data that include the messages published by ordinary users and D. Trump's team on Twitter platform in March – October 2020. The application of the authors' technique has resulted in discursive fields visualization, abnormal discursive activity areas identification, the interaction of discourses within the discursive field description, the mode of messages and their recurrence level determination. It is shown that the analysis of Internet communication using the developed methodology contribute to understanding the essence of socio-political and socio-economic processes and deepening the predictive analytics of their development, and can also be used for discursive management in order to strengthen constructive and neutralize destructive social practices in online space.

Key words: networked linguistic data, discursive fields, graph theory, network modelling, network linguistics.

Citation. Malysheva O.P., Ryabchenko N.A. Networked Linguistic Data and Discourse Management: The 2020 US Presidential Election. Vestnik Volgogradskogo gosudarstvennogo universiteta. Seriya 2. Yazykoznanie [Science Journal of Volgograd State University. Linguistics], 2022, vol. 21, no. 3, pp. 39-53. (in Russian). DOI: https://doi.org/10.15688/jvolsu2.2022.3.4

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