The Rhetorical Impact of Polylingualism Employed by Lithuanian Politicians on Facebook

Q2 Arts and Humanities Respectus Philologicus Pub Date : 2022-10-07 DOI:10.15388/respectus.2022.42.47.104
Eglė Gabrėnaitė, Skirmantė Biržietienė
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Abstract

The aim of the research presented in this article aims to determine the impact of polylingualism on the effectiveness of political rhetoric in Lithuania. The study focuses on elements borrowed from other languages and used by Lithuanian politicians in their Facebook posts. In addition, the motivation behind such use is explored, aiming to establish whether polylingualism is part of a conscious effort of political communication in order to build a positive image. Within the scope of this research are Facebook posts containing cases of polylingualism, specifically, English-language inserts. The authors of these posts are prominent politicians who are native Lithuanian speakers engaged in active communication on social media. Collected during the period of 2018–2021, the research material was examined using the method of rhetorical discourse analysis, resulting in the identification of characteristic instruments of persuasion, i.e. the tools which help enhance the effectiveness of certain discourse. The researchers aimed to determine the general patterns and dominant tendencies of mixed speech within the political discourse on social media. The research reveals the use of polylingualism as a stylistic tool imitating informal speaking and creating contextual discourse.
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立陶宛政治家在Facebook上使用多语言的修辞影响
本文提出的研究目的是确定多语言主义对立陶宛政治修辞有效性的影响。这项研究的重点是立陶宛政客在脸书帖子中借用其他语言使用的元素。此外,还探讨了这种使用背后的动机,旨在确定多语主义是否是有意识的政治沟通努力的一部分,以建立积极的形象。在这项研究的范围内,Facebook上的帖子包含了多种语言的案例,特别是英语插入。这些帖子的作者都是以立陶宛语为母语的知名政治家,他们在社交媒体上积极交流。收集于2018-2021年期间的研究材料,使用修辞话语分析的方法对其进行了检验,从而确定了具有特征的说服工具,即有助于提高某些话语有效性的工具。研究人员旨在确定社交媒体上政治话语中混合言论的一般模式和主导趋势。本研究揭示了多元语言作为一种文体工具的使用,它模仿了非正式口语并创造了语境话语。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Respectus Philologicus
Respectus Philologicus Arts and Humanities-Literature and Literary Theory
CiteScore
0.30
自引率
0.00%
发文量
31
审稿时长
12 weeks
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