A corpus-assisted cognitive analysis of metaphors in the Arabic subtitling of English TV series

<p dir="ltr">This paper reports on the findings of a study that aimed at investigating the conceptual metaphors used in the Arabic subtitling of 150 English TV series (1982–2017), adopting Conceptual Metaphor Theory (CMT) proposed by Lakoff and Johnson (1980) for data analysis. The d...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Ronza Abu Rumman (17944943) (author)
مؤلفون آخرون: Ahmad S. Haider (17900039) (author), Sane Yagi (17944946) (author), Amer Al-Adwan (17316982) (author)
منشور في: 2023
الموضوعات:
الوسوم: إضافة وسم
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الوصف
الملخص:<p dir="ltr">This paper reports on the findings of a study that aimed at investigating the conceptual metaphors used in the Arabic subtitling of 150 English TV series (1982–2017), adopting Conceptual Metaphor Theory (CMT) proposed by Lakoff and Johnson (1980) for data analysis. The data were examined by using WordSmith Tools (Scot 2012) which is compatible with Arabic data. The study revealed that the most frequently used source domains in the corpus were journey, building, war, illness, plants, and machine, respectively; whereas, the least frequently used source domains were body parts, game, water, supernatural creatures, fabrics, fire, and light, respectively. Besides, the most commonly used type of conceptual metaphor is structural metaphor. The study concluded that the vast majority of metaphorical expressions are lexicalized and conventional to make the subtitling easily accessible to the reader. The study recommends that future studies be conducted on the translation strategies adopted in subtitling English metaphors into Arabic.</p><h2>Other Information</h2><p dir="ltr">Published in: Cogent Social Sciences<br>License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1080/23311886.2023.2231622" target="_blank">https://dx.doi.org/10.1080/23311886.2023.2231622</a></p>