Published December 20, 2021 | Version v1
Journal article Open

NEOLOGISM IN ENGLISH-ARABIC TRANSLATION OF INFORMATION TECHNOLOGY TERMS

  • 1. Research Centre for Arabic Language and Islamic Civilization, Faculty of Islamic Studies, Universiti Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia.

Description

Technological advancements have aided in the expansion of a languages vocabulary through the addition of new items. Naming items can be accomplished during the translation process by constructing a diverse structure of neologisms. The purpose of this study was to analyse the results of technical term translations from English to Arabic in the field of Information Technology (IT) and to ascertain the frequency with which Arabic neologisms are published as a result of the process. Additionally, the study identified factors that influence the formation of neologisms through the translation process of translators. The study analysed data from the ProZ.com website regarding IT terms. The data were analysed by dividing the source term into a variety of neologism structures, such as derivatives, blended, compound, and acronym. The research was conducted using al-Sihabis theoretical framework for word formation, which classified word formation into two categories: Morphological Neologism, which refers to the process of word development, and Loan Neologism, which refers to the process of converting foreign language words to Arabic. The findings indicate that ProZ.com translators took one of two approaches to the formation of Arabic neologism: they either altered the original structure of the source term or preserved it as the structure of Arabic neologism. Nonetheless, 44% of the data wereconverted to compound form. While the majority of other neological structures are derived from the original structure of the source language. The structure of such neologisms is shaped by the translators translation process. Translators frequently translate data literally in order to preserve the source language neologism in its original form, according to studies. However, 25% of data were translated using descriptive and functional equivalence, while 13.1% of data were translated using the Arabization process, which converts source language terms that lack an Arabic equivalent.

 

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