تقييم تقنيات الترجمة ChatGPT 4.0 لتحسين جودة ترجمة أخبار كرة القدم على موقع سبق

المؤلفون

DOI:

https://doi.org/10.35516/Hum.2026.10146

الكلمات المفتاحية:

الترجمة الرقمية، تقنيات الترجمة، جودة الترجمة، أخبار كرة القدم، ChatGPT 4.0، موقع سبق.

الملخص

الأهداف: تهدف هذه الدراسة إلى وصف تقنيات الترجمة وقياس وتقييم جودة الترجمة المستخدمة من قبل ChatGPT 4. 0 في أخبار كرة القدم على موقع سبق كمحاولة لتحسين مصداقية الترجمة الرقمية.

المنهج: تستخدم هذه الدراسة المنهج الكيفي باستخدام نظرية تقنية الترجمة لمولينا البير ونظرية جودة الترجمة لنبابان، وتأتي بيانات بحث الجودة من ثلاثة مبحوثين من طلاب تخصص الترجمة في جامعة صيرف هداية الله الإسلامية الحكومية بجاكرتا.

النتائج: حددت هذه الدراسة ثماني تقنيات ترجمة مستخدمة من قبل ChatGPT 4.0 في ترجمة أخبار كرة القدم من موقع سبق دوت أورج، حيث كانت تقنية التضخيم هي التقنية الأكثر استخدامًا (34.37%) وتقنية الاختزال هي التقنية الأقل استخدامًا (1.03%). بلغت درجة الجودة النهائية 2.62، مما يشير إلى جودة الترجمة الجيدة من حيث الدقة وسهولة القراءة والمقبولية. من بين 90 نقطة بيانات، كانت 83.3% من نقاط البيانات ذات مستوى عالٍ من قابلية القراءة، و72.2% كانت دقيقة ومقبولة.

الخلاصة: تُظهر النتائج أن ChatGPT 4.0 قادر على إنتاج ترجمات عالية الجودة للأخبار الرياضية، لكن يظل التدخل البشري ضروريًا للتعامل مع الفروق الثقافية الدقيقة وضمان دقة السياق. وتسلط هذه الدراسة الضوء على أهمية التعاون بين أدوات الذكاء الاصطناعي والمترجمين البشريين لتحقيق الجودة المثلى للترجمة، خاصة في المجالات المتخصصة مثل الأخبار الرياضية.

التنزيلات

تنزيل البيانات ليس متاحًا بعد.

المراجع

Akbari, A., & Shahnazari, M. (2015). The rejuvenation of equivalence paradigm in literary texts: Equimediation as the Seul et alleiniges paradigm in translation. Mediterranean Journal of Social Sciences, 6(4S2), 438–447. https://doi.org/10.5901/mjss.2015.v6n4s2p438

Al-Laith, A., & Shahbaz, M. (2021). Tracking sentiment towards news entities from Arabic news on social media. Future Generation Computer Systems, 118, 467–484. https://doi.org/10.1016/j.future.2021.01.015

Al-Salman, S., & Haider, A. S. (2024). Assessing the accuracy of MT and AI tools in translating humanities or social sciences Arabic research titles into English: Evidence from Google Translate, Gemini, and ChatGPT. International Journal of Data and Network Science, 8(4), 1940–1958. https://doi.org/10.5267/j.ijdns.2024.5.009

Alhawarat, M., & Aseeri, A. O. (2020). A Superior Arabic Text Categorization Deep Model (SATCDM). IEEE Access, 8, 24653–24661. https://doi.org/10.1109/ACCESS.2020.2970504

Amelia, R. D., Ningshi, T. W. R., & Ayesa, A. (2023). Translation Techniques for Indonesian Online Media News Headlines into Chinese. Journal of Mandarin Horizons, 7(1), 61. https://doi.org/10.36279/apsmi.v7i1.199

Andrew, M., Finnegan, L., Datson, N., & Dugdale, J. H. (2022). Men Are from Quartile One, Women Are from? Relative Age Effect in European Soccer and the Influence of Age, Success, and Playing Status. Children, 9(11). https://doi.org/10.3390/children9111747

Ardi, H. (2015). Introduction to translation (Issue November 2018). https://doi.org/10.31227/osf.io/mwz2q

Brook, J. (2012). The Role of Translation in the Production of International Print News. Three Case Studies in the Language Direction Spanish to English. 1994, 248.

https://researchspace.auckland.ac.nz/bitstream/handle/2292/19462/whole.pdf?sequence=2%5Cnhttps://researchspace.auckland.ac.nz/handle/2292/19462

Catford, J. (1965). Theory of Translation. In Pliego de Yuste (Vol. 1, Issue 4).

http://www.pliegosdeyuste.eu/n4pliegos/eugeneanida.pdf

Corcho, O., Priyatna, F., & Chaves-Fraga, D. (2020). Towards a new generation of ontology based data access. Semantic Web, 11(1), 153–160. https://doi.org/10.3233/SW-190384

Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239

https://doi.org/10.1080/14703297.2023.2190148

Dewi Ambarastuti, R. (2018). Analysis of the translation technique of Japanese folklore text Nezumi no Sumo into rat Indonesian and sumo on Www.Jitco.or.Jp site. JLT – Journal of Applied Linguistics of the State Polytechnic of Malang, 8(1), 1–23.

Dong, Y. (2022). Introduction to Translations. In Curator (Vol. 65, Issue 2). https://doi.org/10.1111/cura.12479

El Rifai, H., Al Qadi, L., & Elnagar, A. (2022). Arabic text classification: the need for multi-labeling systems. Neural Computing and Applications, 34(2), 1135–1159. https://doi.org/10.1007/s00521-021-06390-z

ElFqih, K., & Monti, J. (2024). Large Language Models as Legal Translators of Arabic Legislatives. 111–122. https://aclanthology.org/2024.arabicnlp-1.10/

Et, B., Bête, L., Barbot, K., Nurul, A., & Hartaji, S. (2024). Analysis of Amplification Translation Techniques in Novel La. 10(4), 3719–3728.

Fraser, H., Crossland, D., Bacher, I., Ranney, M., Madsen, T., & Hilliard, R. (2023). Comparison of Diagnostic and Triage Accuracy of Ada Health and WebMD Symptom Checkers, ChatGPT, and Physicians for Patients in an Emergency Department: Clinical Data Analysis Study. JMIR MHealth and UHealth, 11(1), 1–10. https://doi.org/10.2196/49995

Fu, Z., He, X., Wang, E., Huo, J., Huang, J., & Wu, D. (2021). Personalized human activity recognition based on integrated wearable sensor and transfer learning. Sensors (Switzerland), 21(3), 1–23. https://doi.org/10.3390/s21030885

Guerrero-Calderón, B. (2021). The effect of short-term and long-term coronavirus quarantine on physical performance and injury incidence in high-level soccer. Soccer and Society, 22(1–2), 85–95 https://doi.org/10.1080/14660970.2020.1772240.

Irma, A., & Ubaidillah. (2023). Reduction Techniques in Arabic-Indonesian Imperative and Nominal Sentence Translation. Al-Ittijah : Journal of Arabic Language Science and Education, 15(1), 64–78. https://doi.org/10.32678/alittijah.v15i1.8280

JASMINE, K. (2014). Meaning - Based Translation. In addition of sodium benzoate and potassium sorbate (antiinversion) and stirring speed as an effort to inhibit inversion reactions in sugarcane.

Jiao, H., Peng, B., Zong, L., Zhang, X., & Li, X. (2024). Gradable ChatGPT Translation Evaluation. Procesamiento del Lenguaje Natural, 72, 73–85. https://doi.org/10.26342/2024-72-5

Khoshafah, F. (2023). ChatGPT for Arabic-English Translation: Evaluating the Accuracy ChatGPT for Arabic-English Translation: Evaluating the Accuracy. Research Square, 0–19. https://doi.org/10.21203/rs.3.rs-2814154/v2

Kubayi, A., & Larkin, P. (2020). Technical performance of soccer teams according to match outcome at the 2019 FIFA Women's World Cup. International Journal of Performance Analysis in Sport, 20(5), 908–916. https://doi.org/10.1080/24748668.2020.1809320

Lestari, W., Yoyo, Y., & Zaini, A. R. (2020). Amplification and Description Techniques in the Translation of Arabic Phrases in Matan Al-Ghayah wa Al-Taqrib. Izdihar : Journal of Arabic Language Teaching, Linguistics, and Literature, 3(2), 113–128. https://doi.org/10.22219/jiz.v3i2.12337

Lim, Z. W., Pushpanathan, K., Yew, S. M. E., Lai, Y., Sun, C. H., Lam, J. S. H., Chen, D. Z., Goh, J. H. L., Tan, M. C. J., Sheng, B., Cheng, C. Y., Koh, V. T. C., & Tham, Y. C. (2023). Benchmarking large language models' performances for myopia care: a comparative analysis of ChatGPT-3.5, ChatGPT-4.0, and Google Bard. EBioMedicine, 95, 104770. https://doi.org/10.1016/j.ebiom.2023.104770

Manakhimova, S., Avramidis, E., Macketanz, V., Lapshinova-Koltunski, E., Bagdasarov, S., & Möller, S. (2023). Linguistically Motivated Evaluation of the 2023 State-of-the-art Machine Translation: Can GPT-4 Outperform NMT? Conference on Machine Translation - Proceedings, 224–245. https://doi.org/10.18653/v1/2023.wmt-1.23

Mardiana, W. (2014). Transposition and modulation techniques: equivalence and shift in the translation of the short story titled "My Beloved Edith." Parole: Journal of Linguistics and Education, 4(2 Oct), 120–130.

Miles, M. B., & Huberman, A. M. (1994). Qualitative Data Analysis. Sage Publication.

Molina, L., & Albir, A. H. (2002). Translation techniques revisited: A dynamic and functionalist approach. Meta, 47(4), 498–512. https://doi.org/10.7202/008033ar

Nababan, M., Nuraeni, A., & Sumardiono. (2012). Development of a Translation Quality Assessment Model. Linguistic and Literary Studies, 24(1), 39–57.

Naratama, B. B. (2017). Analysis of BBC Indonesia News Translation Strategy and Its Influence on Translation Quality. JLT – Journal of Applied Linguistics of the State Polytechnic of Malang, 7(1), 10–27. https://medium.com/@arifwicaksanaa/pengertian-use-case-a7e576e1b6bf

Ningsih, R. ., Pulungan, A. H., & . Z. . (2021). the Assessment of Translation Quality in Bound Novel. Applied Linguistics, 17(3), 258. https://doi.org/10.24114/lt.v17i3.22452

Niron, Y. M. L. (2024). Assessment of translation of analytical texts, comparison of translated texts, and evaluation of translations. Journal of Linguistics, 12(1), 21–30. https://ejurnal.undana.ac.id/index.php/bianglala

Popel, M., Tomkova, M., Tomek, J., Kaiser, Ł., Uszkoreit, J., Bojar, O., & Žabokrtský, Z. (2020). Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals. Nature Communications, 11(1), 1–15. https://doi.org/10.1038/s41467-020-18073-9

Popović, M. (2018). Error Classification and Analysis for Machine Translation Quality Assessment (Issue June). https://doi.org/10.1007/978-3-319-91241-7_7

Pushpanathan, K., Lim, Z. W., Er Yew, S. M., Chen, D. Z., Hui'En Lin, H. A., Lin Goh, J. H., Wong, W. M., Wang, X., Jin Tan, M. C., Chang Koh, V. T., & Tham, Y. C. (2023). Popular large language model chatbots' accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries. IScience, 26(11), 108163. https://doi.org/10.1016/j.isci.2023.108163

Sadeq, M. A., Ghorab, R. M. F., Ashry, M. H., Abozaid, A. M., Banihani, H. A., Salem, M., Aisheh, M. T. A., Abuzahra, S., Mourid, M. R., Assker, M. M., Ayyad, M., & Moawad, M. H. E. D. (2024). AI chatbots show promise but limitations on UK medical exam questions: a comparative performance study. ScienSadeq, M. A., Ghorab, R. M. F., Ashry, M. H., Abozaid, A. M., Banihani, H. A., Salem, M., Aisheh, M. T. A., Abuzahra, S., Mourid, M. R., Assker, M. M., Ayyad, M., & Moawad, M. H. E. D. (2024). AI Chatbots Show Promise but Limitations on UK Medical Ex, 14(1), 1–11. https://doi.org/10.1038/s41598-024-68996-2

Shuttleworth, M. (2014). Dictionary of Translation Studies. In Dictionary of Translation Studies. https://doi.org/10.4324/9781315760490

Syihabuddin. (2016). Arabic-Indonesian Translation Theory and Practice. In Journal of Chemical Information and Modeling.

Tian, S., Jia, L., & Zhang, Z. (2023). Investigating students' attitudes towards translation technology: The status quo and structural relations with translation mindsets and future work self. Frontiers in Psychology, 14(February), 1–16. https://doi.org/10.3389/fpsyg.2023.1122612

Valdeón, R. A. (2022). Gatekeeping, ideological affinity and journalistic translation. Journalism, 23(1), 117–133. https://doi.org/10.1177/1464884920917296

Wordpress, •, Rachmawati, R., Language, B., Riau, P., Education, K., Culture, D., & Binawidya, J. (n.d.). TRANSLATION TECHNIQUES AND IDEOLOGIES IN WORDPRESS. 211–224. https://id.wikipedia.org/wiki/WordPress

Zakraoui, J., Saleh, M., Al-Maadeed, S., & Alja'am, J. M. (2021). Arabic Machine Translation: A Survey with Challenges and Future Directions. IEEE Access, 9, 161445–161468. https://doi.org/10.1109/ACCESS.2021.3132488

Zhang, J. J., & Zong, C. Q. (2020). Neural machine translation: Challenges, progress and future. Science China Technological Sciences, 63(10), 2028–2050. https://doi.org/10.1007/s11431-020-1632-x.

التنزيلات

منشور

2026-10-01

إصدار

القسم

الإعلام

كيفية الاقتباس

Farhan, M., Mubarok, M. Z., Abshar, U., Suparno, D., Tsaqofi, W. A., & Hifni, A. (2026). تقييم تقنيات الترجمة ChatGPT 4.0 لتحسين جودة ترجمة أخبار كرة القدم على موقع سبق. دراسات: العلوم الإنسانية والاجتماعية, 54(1), 10146. https://doi.org/10.35516/Hum.2026.10146