SEMANTIC MOTIVATION OF THE TERMINOLOGIZED LEXIS IN THE FIELD OF DIGITAL TECHNOLOGIES

Autor: Vilija Celiešienė, Saulute Juzeleniene
Rok vydání: 2020
Předmět:
Zdroj: Journal of Teaching English for Specific and Academic Purposes. :031
ISSN: 2334-9212
2334-9182
DOI: 10.22190/jtesap2001031c
Popis: Digital technologies are changing people’s lives, the way we communicate, learn and work. Modern language teaching technologies are changing the ways we learn languages as well. On the other hand, the language itself is changing as technology advances. The aim of this article is to reveal semantic motivation of terminologized Lithuanian and English computer lexis. The present research, focusing on semantic motivation of IT terms, is also aimed at identifying similarities and differences between the semantic models of the words in both contacting languages, and revealing the factors that determine the choice of foreign sememes. In addition, the article sheds some light on semantic relations of IT terms, as well as on tendencies in the shifts of meanings of specific LT and EN common language words, related to the process of terminologization. It has been established that the majority of the analysed words that have entered the Lithuanian IT vocabulary as a result of terminization and transterminization processes can be considered semantic loan-translations, having acquired new meanings from foreign (usually English) words, and based on ‘borrowed’ motivation. Nonetheless, many such words can also be substantiated in Lithuanian, for their terminological meanings can be explained by central, nonterminological meanings. Thus, in the majority of cases, close associations between central meanings of specific English and Lithuanian words have stimulated the development of new terminological meanings related to information technologies. By contrast, only a relatively small number of the analysed Lithuanian terms can be considered semantic formations, having acquired their terminological meanings in the process of turning Lithuanian common language words into terms.
Databáze: OpenAIRE