Strategies of translating swear words into Arabic: a case study of a parallel corpus of Netflix English-Arabic movie subtitles

Hussein Abu-Rayyash, Ahmad S. Haider and Amer Al-Adwan ()
Additional contact information
Hussein Abu-Rayyash: Kent State University
Ahmad S. Haider: Applied Science Private University
Amer Al-Adwan: Hamad Bin Khalifa University

Palgrave Communications, 2023, vol. 10, issue 1, 1-13

Abstract: Abstract This study adopts a corpus-assisted approach to explore the translation strategies that Netflix subtitlers opted for in rendering 1564 English swear words into Arabic. It uses a 699,229-word English-Arabic parallel corpus consisting of the English transcriptions of forty English movies, drama, action, science fiction (sci-fi), and biography and their Arabic subtitles. Using the wordlist tool in SketchEngine, the researchers identified some frequent swear words, namely fuck, shit, damn, ass, bitch, bastard, asshole, dick, cunt, and pussy. Moreover, using the parallel concordance tool in SketchEngine revealed that three translation strategies were observed in the corpus, namely, omission, softening, and swear-to-non-swear. The omission strategy accounted for the lion’s share in the investigated data, with 66% for drama, 61% for action, 52% for biography, and 40% for sci-fi. On the other hand, the swear-to-non-swear strategy was the least adopted one, accounting for 21% in sci-fi, 16% in biography, 14% in drama, and 11% in action. In addition, the softening strategy got the second-highest frequency across the different movie genres, with 39% for sci-fi, 32% for biography, 28% for action, and 20% for drama. Since swear words have connotative functions, omitting or euphemizing them could cause a slight change in the representation of meaning and characters. The study recommends more corpus-assisted studies on different AVT modes, including dubbing, voiceover, and free commentaries.

Date: 2023
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1057/s41599-023-01506-3 Abstract (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pal:palcom:v:10:y:2023:i:1:d:10.1057_s41599-023-01506-3

Ordering information: This journal article can be ordered from
https://www.nature.com/palcomms/about

DOI: 10.1057/s41599-023-01506-3

Access Statistics for this article

More articles in Palgrave Communications from Palgrave Macmillan
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().