JOURNAL ARTICLE

Translating customer identity in male cosmetics advertising.

  • Published In: Translation & Translanguaging in Multilingual Contexts (TTMC), 2024, v. 10, n. 3. P. 288 1 of 3

  • Database: Communication Source 2 of 3

  • Authored By: Eikosideka, Aikaterini 3 of 3

Abstract

Addressee identity awareness often affects how speakers structure discourses. The study views male cosmetics advertising through a pragmatic lens to investigate how customer identity is shaped cross-culturally through men's deodorant advertisements on the English and Greek market. The study uses communication styles (Hofstede, Hofstede, and Minkov 2010) to account for (a) naturalistic translation shifts in verbal or multimodal data which tend to improve product reception in the Greek target context and (b) experimental data to confirm how masculinity is shaped and attributed to male customers by well renowned deodorant companies. The data analysis reveals that socio-pragmatic parameters are operative in accounting for differences in the two contexts. Findings show cross-cultural variation along three of Hofstede, Hofstede, and Minkov's (2010) communication styles, namely, individualism/collectivism, masculinity/femininity and uncertainty avoidance/tolerance, correlating it with a fourth dimension of the framework, the high/low power distance one. The significance of the research lies in that it shows how commercial content producers register locally shared gender identity assumptions relevant to the audience type they address. Translation is another platform where pragmatic variation may be fruitfully explored cross-culturally. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Translation & Translanguaging in Multilingual Contexts (TTMC). 2024/09, Vol. 10, Issue 3, p288
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2024
  • ISSN:2352-1805
  • DOI:10.1075/ttmc.00140.eik
  • Accession Number:180117368
  • Copyright Statement:Copyright of Translation & Translanguaging in Multilingual Contexts (TTMC) is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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