Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ South Ural State Uni...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Репрезентация вербальной агрессии в публичном политическом дискурсе

Authors: Torbik, E.M.;

Репрезентация вербальной агрессии в публичном политическом дискурсе

Abstract

Торбик Елена Михайловна, кандидат филологических наук, доцент, доцент Департамента английского языка и профессиональной коммуникации, Финансовый университет при Правительстве РФ, Москва, Россия; elena_torbik@mail.ru Elena M. Torbik, PhD in Philology, Associate Professor of the Department of the English Language and Professional Communication, Financial University under the Government of the Russian Federation, Moscow, Russia, elena_torbik@mail.ru Целью статьи является выявление лингвостилистических средств проявления вербальной агрессии в американском публичном политическом дискурсе на материале скриптов видеообращений Дж. Байдена касательно специальной военной операции на Украине за период февраль 2022 г. – июнь 2023 г. Поскольку современная речевая культура характеризуется отказом от прямых проявлений агрессии в публичном политическом дискурсе, в исследовании продемонстрированы более приемлемые формы. Среди них – ярлыки, являющиеся политическими пейоративами; речевые акты обвинений и осуждений; оценочные суждения, объектом которых являются намерения и действия России в условиях специальной военной операции на Украине, последствия этих действий для обеих сторон, деятельность и взгляды В.В. Путина, его личность. Аргументация, сопровождающая оценки Джо Байдена, охарактеризована в работе как псевдоаргументация, поскольку в ней преподносится вариативная интерпретация действительности. С позиции коммуникативной лингвистики вербальная агрессия в речи действующего президента США реализуется в рамках стратегии дискредитации через оппозицию «свой» / «чужой». В целом вербальная агрессия способствует осуществлению манипулятивного воздействия на аудиторию. The purpose of the article is to identify linguistic and stylistic means of verbal aggression in American public political discourse. The study is based on the scripts of J. Biden's video messages regarding the special military operation in Ukraine, released from February 2022 to June 2023. Since modern speech culture rejects direct manifestation of aggression in public political discourse, the study demonstrates more acceptable forms of aggression. These include labels that are political pejoratives, speech acts of accusation and condemnation, and evaluative judgements. The objects of the latter are the intentions and actions of Russia in the context of the special military operation in Ukraine, the consequences of these actions for both sides, the activities and views of Vladimir Putin, and his personality. The argumentation accompanying Joe Biden's evaluative judgements is characterized as pseudo-argumentation since it presents a variable interpretation of reality. In terms of communicative linguistics, verbal aggression in the speech of the current US president is implemented as part of a discrediting strategy through the opposition of “own” vs. “alien”. In general, verbal aggression contributes to the implementation of manipulative influence on the audience.

Keywords

дискредитация, политический дискурс, influence, invective, evaluation, political discourse, аргументация, вербальная агрессия, воздействие, verbal aggression, discrediting, argumentation, manipulation, инвектива, манипуляция, оценочность, УДК 8.81

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green