Audience Responses to Cultural and Linguistic Gaps in English–Arabic Auto-Subtitles on YouTube

Main Article Content

Abdullah Al-Momani
Ahmad S Haider
Mohammed Dagamseh
Wala' Mohammad Akasheh

Abstract

This study investigates audience reception of English–Arabic auto-generated subtitles on YouTube, focusing on linguistic accuracy, cultural representation, trust, and viewing experience. A large-scale survey of 4,500 participants across diverse age groups, genders, and linguistic backgrounds was conducted to examine demographic and behavioral factors shaping subtitle use. Descriptive results revealed that YouTube is firmly embedded in daily routines, with 72.4% of respondents integrating it into everyday media habits. Subtitles were widely relied upon, with nearly 60% routinely enabling them, and motivations included clarifying unclear audio (68.2%), navigating accents (61.9%), and supporting language learning (54.3%). However, mistranslations and cultural misrepresentations were highly salient, with over 70% noticing linguistic errors and 66.5% reporting missed cultural references, both of which significantly reduced enjoyment and comprehension. Trust in auto-generated subtitles was conditional: fewer than half expressed blanket trust, while 73% preferred human-translated subtitles, and trust varied strongly by content type, being lower for educational and formal material. Inferential analyses showed that proficiency in English reduced sensitivity to linguistic errors, while proficiency in Arabic heightened awareness of cultural mistranslations. Frequent viewers and those with strong media habits reported greater reliance on subtitles, while motivations such as accessibility and language learning predicted consistent use. The findings highlight both the indispensability and limitations of auto-subtitles, emphasizing their role as accessibility tools while exposing persistent deficiencies in linguistic accuracy and cultural mediation. These insights have implications for AI translation design, user trust, and media accessibility in multilingual digital environments.

Downloads

Download data is not yet available.

Article Details

How to Cite
Al-Momani, A., Haider, A. S., Dagamseh, M. ., & Akasheh, W. M. . (2025). Audience Responses to Cultural and Linguistic Gaps in English–Arabic Auto-Subtitles on YouTube. Research Journal in Advanced Humanities, 6(3). https://doi.org/10.58256/x3sten23
Section
Articles

How to Cite

Al-Momani, A., Haider, A. S., Dagamseh, M. ., & Akasheh, W. M. . (2025). Audience Responses to Cultural and Linguistic Gaps in English–Arabic Auto-Subtitles on YouTube. Research Journal in Advanced Humanities, 6(3). https://doi.org/10.58256/x3sten23

Share

References

Abulawi, F., Al Salman, S., & Haider, A. S. (2022). Modern Standard Arabic vs. Egyptian Vernacular in dubbing animated movies: A case study of A Bug’s Life. The International Journal of Communication and Linguistic Studies, 21(1), 125-141. doi:https://doi.org/10.18848/2327-7882/cgp/v21i01/125-141

Akasheh, W. M., Haider, A. S., Al-Saideen, B., & Sahari, Y. (2024). Artificial intelligence-generated Arabic subtitles: insights from Veed. io's automatic speech recognition system of Jordanian Arabic. Texto Livre, 17, e46952-e46952. doi:10.1590/1983-3652.2024.46952.

Al-Abbas, L. S., Haider, A. S., & Saideen, B. (2022). A quantitative analysis of the reactions of viewers with hearing impairment to the intralingual subtitling of Egyptian movies. Heliyon, e08728. doi:https://doi.org/10.1016/j.heliyon.2022.e08728

Al-Darabee, M. (2024). Human and Machine-generated Arabic Subtitles: A case study of Taboo Expressions in the English Movie "The Wolf of Wall Street". (Unpublished MA Thesis). Applied Science Private University, Amman-Jordan.

Al-Zgoul, O., & Al-Salman, S. (2022). Fansubbers’ Subtitling Strategies of Swear Words from English into Arabic in the Bad Boys Movies. Open Cultural Studies, 6(1), 199-217. doi:https://doi.org/10.1515/culture-2022-0156

Aldualimi, M., & Almahasees, Z. (2022). A Quantitative Analysis of the Reactions of Viewers to the Subtitling the Arabic Version of Ar-Risalah's Movie" The Message" in English. Journal of Southwest Jiaotong University, 57(6), 1053-1063. doi:https://doi.org/10.35741/issn.0258-2724.57.6.91

Ali, S., Al-Jabri, H., AL-Adwan, A., & Eliza Abdul Rahman, W. R. (2024). Subtitling Saudi Arabic slang into English: the case of “The Book of the Sun” on Netflix. Humanities and Social Sciences Communications, 11(1), 1-7.

Alkhatib, R., & Haider, A. S. (2024). Subtitling Legal Expressions in English Series into Arabic by Netflix, Machine, and Artificial Intelligence. Pakistan Journal of Criminology, 14(4), 513-528. doi:https://doi.org/10.62271/pjc.16.4.513.528

Allam, A. (2023). Quality Assessment of Interlingual YouTube Auto-generated Closed Captions in Some Crime Narratives Applying the NTR Model. Textual Turnings: An International Peer-Reviewed Journal in English Studies, 5(2), 59-83.

Almahasees, Z. (2017). Machine Translation Quality of Khalil Gibran’s The Prophet. AWEJ for translation & literary studies, 1(4), 151-159. doi:10.2139/ssrn.3068518

Almahasees, Z. (2018). Assessment of Google and Microsoft Bing translation of journalistic texts. International Journal of Languages, Literature and Linguistics, 4(3), 231-235.

Almahasees, Z. (2021). Analysing English-Arabic Machine Translation: Google Translate, Microsoft Translator and Sakhr. London: Routledge.

Almahasees, Z., & Jaccomard, H. (2020). Facebook Translation Service (FTS) Usage among Jordanians during COVID-19 Lockdown. Advances in Science, Technology and Engineering Systems Journal, 5(6), 514-519. doi:10.25046/aj050661

Altunisik, E., Firat, Y. E., & Keceli, Y. K. (2022). Content and quality analysis of videos about multiple sclerosis on social media: the case of YouTube. Multiple Sclerosis and Related Disorders, 65, 104024.

Alzaabi, S., & Rabab’ah, G. (2023). Conceptual metaphors in YouTube auto-generated subtitles: BBC travel show as a case. The International Journal of Humanities Education, 22(1), 57.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334. doi:https://doi.org/10.1007/bf02310555

Darwish, N., Haider, A. S., Alantari, D., Saed, H., Tannous, B., & Dagamseh, M. (2025). A Reception Study of AI-Translated Idioms and Proverbs between Arabic and English. Research Journal in Advanced Humanities, 6(3), 1-14.

Debbas, M., & Haider, A. S. (2020). Overcoming cultural constraints in translating English series: A case study of subtitling family guy into Arabic. 3L, Language, Linguistics, Literature, 26(1), 1-17. doi:https://doi.org/10.17576/3l-2020-2601-01

Di Giovanni, E. (2020). Reception Studies and Audiovisual Translation. In Ł. Bogucki & M. Deckert (Eds.), The Palgrave Handbook of Audiovisual Translation and Media Accessibility (pp. 397-413). Cham: Springer International Publishing.

Du, J., & Lu, J. (2024). A Comparative Study on the Translation Quality between Human and Machine-Generated Subtitles. Paper presented at the 2024 6th International Conference on Natural Language Processing (ICNLP).

Farghal, M. (1999). Failing the Discourse in Translation: A Schematic Perspective. International Journal of Translation, 1(2), 85-102.

Farghal, M., & Shunnaq, A. (1999). Translation with reference to English and Arabic. Irbid: Dar Al-Hilal for Translation.

Gambier, Y. (2003). Screen transadaptation: Perception and reception. The Translator, 9, 171–189.

Gambier, Y. (2018). Translation studies, audiovisual translation and reception. Reception studies in audiovisual translation, 43-66.

Gaule, M., & Josan, G. S. (2012). Machine translation of idioms from english to Hindi. International Journal of Computational Engineering Research, 2(6), 50-54.

Haider, A. S., & Al-Salman, S. (2022). The Effects of Intralingual Subtitles on Jordanian University Students’ Foreign Language Learning. International Journal of Instruction, 15(4), 57–76.

Haider, A. S., & AlKhatib, R. (2025). Evaluating Netflix, Machine, and Artificial Intelligence Subtitling of Arabic Legal Expressions into English. Comparative Legilinguistics.

Haider, A. S., Alzghoul, O., & Hamadan, Y. (2023). Creating and Experimenting a New Parallel Corpus of English-Arabic Subtitles of Culinary Shows: A Useful Guide for Translating Food Across Cultures. World Journal of English Language, 13(8), 358-372. doi:https://doi.org/10.5430/wjel.v13n8p358

Haider, A. S., & Hussein, R. F. (2022). Modern Standard Arabic as a Means of Euphemism: A Case Study of the MSA Intralingual Subtitling of Jinn Series. Journal of Intercultural Communication Research, 51(6), 628-643. doi:https://doi.org/10.1080/17475759.2022.2106289

Haider, A. S., & Shohaibar, R. S. (2024). Netflix English subtitling of idioms in Egyptian movies: challenges and strategies. Humanities & Social Sciences Reviews, 11(1), 1-13. doi:https://doi.org/10.1057/s41599-024-03327-4

Hashish, R., & Hussein, R. F. (2022). Strategies Subtitlers Use in Rendering English Slang Expressions Into Arabic. Theory and Practice in Language Studies, 12(4), 752-762. doi:https://doi.org/10.17507/tpls.1204.16

Kim, H., Tao, Y., Liu, C., Zhang, Y., & Li, Y. (2023). Comparing the Impact of Professional and Automatic Closed Captions on Video-Watching Experience. Paper presented at the Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, Hamburg, Germany.

Mehawesh, M. I., & Neimneh, S. S. (2021). Problems in Subtitling Cultural-Bound Expressions in “Theeb” Movie: A Case Study. Theory Practice in Language Studies, 11(10), 1217-1223. doi:https://doi.org/10.17507/tpls.1110.09

Obeidat, M. M. (2023). Translating Culture in the Jordanian TV Comedy Series “al jar gabl al dar”(My American Neighbor) Into English. Sage Open, 13(3), 21582440231197011. doi:https://doi.org/10.1177/21582440231197011

Pfender, E. J., Wanzer, C., & Bleakley, A. (2024). A content analysis of social media influencers’“What I Eat in a day” Vlogs on YouTube. Health Communication, 39(11), 2244-2255.

Rahmatika, R., Yusuf, M., & Agung, L. (2021). The effectiveness of YouTube as an online learning media. Journal of Education Technology, 5(1), 152-158.

Romero-Fresco, P., & Fresno, N. (2023). The accuracy of automatic and human live captions in English. Linguistica Antverpiensia, New Series–Themes in Translation Studies, 22, 114–133. doi:https://doi.org/10.52034/lans-tts.v22i.774

Saed, H. A., Haider, A. S., Al-Salman, S., & Hussein, R. F. (2021). The use of YouTube in developing the speaking skills of Jordanian EFL university students. Heliyon, 7(7).