Discourse technologies in the process of managing electoral preferences during the 2024 US Presidential election campaign
The purpose of the work is to examine the discursive space formed by the top officials of the US political parties from the perspective of the technological nature of verbal management of electoral choices. Methodologically, the study is based on a communicative and psychological approach, with a focus on the psychoanalytic schools of S. Freud and C. Jung. The use of discourse analysis and traditional document analysis has contributed to the direct identification of speech influence tools. The subject area is the mechanisms for achieving a verbal effect on the mindset and behavior patterns of the American electorate during the 2024 US presidential election. The theoretical significance of the study lies in the application of a comprehensive psychoanalytic approach to the examination of the primary political issues of interaction between citizens with active and passive suffrage. The practical significance lies in the identification of ideologized discursive units in the linguistic and semiotic space within the framework of determining the most effective communication strategies that affect the configuration of political forces in the state selected for analysis. The authors concluded that the retransmitted mental concepts have a deterministic influence on the outcome of the election cycle, and that it is important for candidates to have the necessary image for their target audience and to present unified archetypal images that meet the value and material expectations of U.S. citizens regarding the ideal head of state.
Authors
- Dmitriy А. Ezhov (ORCID: https://orcid.org/0000-0002-7103-836X)
- M. A. Gusachenko (ORCID: https://orcid.org/0009-0001-7554-397X)
Institutions
- Financial University (RU)
Publication Details
- Journal
- Journal of Political Research
- Published
- 2025-10-22
- DOI
- https://doi.org/10.12737/2587-6295-2025-9-3-17-34
- Primary Topic
- Discourse Analysis in Language Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00