This corpus-assisted study explores Netflix subtitlers' strategies for translating 1564 English swear words into Arabic, using a 699,229-word parallel corpus of 40 English movies and their Arabic subtitles. Three main strategies were identified: omission (most frequent, varying from 40% to 66% across genres), softening (second most frequent, 20-39%), and swear-to-non-swear (least frequent, 11-21%). The study highlights the impact of cultural constraints and censorship on translation choices and recommends further research on various audiovisual translation modes.

Hussein Abu-Rayyash, Ahmad S. Haider, Amer Al-Adwan