Arabicization via Loan Translation: A Corpus-based Analysis of Neologisms Translated from English into Arabic in the Field of Information Technology

Abstract

Abstract This study aims to use a corpus-based analysis to examine loan translation (LT) as an Arabicization technique in Written Standard Arabic (WSA) for information technology (IT) and investigate the factors impacting LT formation. Data were collected from four corpora: four Arabic online newspapers, the Microsoft Language Portal, two user manuals, and the Arabic Corpus of King Abdul-Aziz City for Science and Technology (KACST). Four LT strategies were identified: morphosyntactic pattern alteration, literal translation, loan blending, and metaphorical extension. Literal translation occurred in three degrees: full LTs, partial LTs, and non-LTs, through calquing. Metaphors based on functional similarity played a crucial role in understanding and accepting IT terms in WSA. Paradigmatic variation prevailed in LTs, with synonymous variations more common than nonsynonymous ones, and no syntagmatic variation. The KACST analysis showed significant differences in occurrence frequency among LT variants. LT formation and variation were influenced by linguistic factors such as lexical need, semantic transparency, and lexical borrowing, as well as extralinguistic factors such as nationalism and lack of coordination among Arabic language academies. The study concludes with implications for addressing the absence of coordination between these academies and improving IT-related LT quality between English and WSA.