A scientometric study of three decades of machine translation research: Trending issues, hotspot research, and co-citation analysis

References

• Allen, J. (2003). Post-editing. Benjamins Translation Library, 35, 297–16. https://doi.org/10.1075/btl.35.19all
   Google Scholar
• Al Mahasees, Z. (2020). Diachronic evaluation of Google Translate, Microsoft Translator, and Sakhr in English-Arabic translation. Unpublished Master’s Thesis, the University of Western Australia,
   Google Scholar
• Andrabi, S. A. B. (2021). A review of machine translation for South Asian low resource languages. Turkish Journal of Computer & Mathematics Education (TURCOMAT), 12(5), 1134–1147. https://doi.org/10.17762/turcomat.v12i5.1777
   Google Scholar
• Aryadoust, V. (2020). A review of comprehension subskills: A scientometrics perspective. System, 88, 102180. https://doi.org/10.1016/j.system.2019.102180
   Web of Science ®Google Scholar
• Brandes, U. (2001). A faster algorithm for betweenness centrality. The Journal of Mathematical Sociology, 25(2), 163–177. https://doi.org/10.1080/0022250X.2001.9990249
   Web of Science ®Google Scholar
• Brown, P. F., Della Pietra, S. A., Della Pietra, V. J., & Mercer, R. L. (1993). The mathematics of statistical machine translation. Parameter estimation.
   Google Scholar
• Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science and Technology, 57(3), 359–377. https://doi.org/10.1002/asi.20317
   Web of Science ®Google Scholar
• Chen, C., Hu, Z., Liu, S., & Tseng, H. (2012). Emerging trends in regenerative medicine: A scientometric analysis in CiteSpace. Expert Opinion on Biological Therapy, 12(5), 593–608. https://doi.org/10.1517/14712598.2012.674507
   PubMed Web of Science ®Google Scholar
• Dong, D., & Chen, M.-L. (2015). Publication trends and co-citation mapping of translation studies between 2000 and 2015. Scientometrics, 105(2), 1111–1128. https://doi.org/10.1007/s11192-015-1769-1
   Web of Science ®Google Scholar
• Editorial. (2017). Editorial. Perspectives, 25(1), 2–3. https://doi.org/10.1080/0907676X.2017.1246219
   Google Scholar
• European Association of Machine Translation. (n.d.) . What is machine translation?. European Association for Machine Translation (eamt.org).
   Google Scholar
• Fiederer, R., & O’Brien, S. (2009). Quality and machine translation: A realistic objective. Journal of Specialised Translation, 11(11), 52–74.
   Google Scholar
• Garcia, I. (2010). Is machine translation ready yet? Target International Journal of Translation Studies, 22(1), 7–21. https://doi.org/10.1075/target.22.1.02gar
   Web of Science ®Google Scholar
• Garcia, I. (2011). Translating by post-editing: Is it the way forward? Machine Translation, 25(3), 217–237. https://doi.org/10.1007/s10590-011-9115-8
   Google Scholar
• Garcia, I., & Pena, M. I. (2011). Machine translation-assisted language learning: Writing for beginners. Computer Assisted Language Learning, 24(5), 471–487. https://doi.org/10.1080/09588221.2011.582687
   Web of Science ®Google Scholar
• Giménez, J., & Màrquez, L. (2010). Asiya: An open toolkit for automatic machine translation (Meta-) evaluation. Fifth Machine Translation Marathon, 94(1). https://doi.org/10.2478/v10108-010-0022-6
   Google Scholar
• Gupta, B. M., & Dhawan, S. M. (2019). Machine translation research: A scientometric assessment of global publications output during 2007-16. DESIDOC Journal of Library & Information Technology, 39(1), 31–38. https://doi.org/10.14429/djlit.39.1.13558
   Web of Science ®Google Scholar
• Huang, Q., & Liu, F. (2019). International translation studies from 2014 to 2018: A bibliometric analysis and its implications. Translation Review, 105(1), 34–57. https://doi.org/10.1080/07374836.2019.1664959
   Web of Science ®Google Scholar
• Kahlon, N. K., & Singh, W. (2021). Machine translation from text to sign language: A systematic review. Universal Access in the Information Society, 22(1), 1–35. https://doi.org/10.1007/s10209-021-00823-1
   Web of Science ®Google Scholar
• Klimova, B., Pikhart, M., Benites, A. D., Lehr, C., & Sanchez-Stockhammer, C. (2022). Neural machine translation in foreign language teaching and learning: A systematic review. Education and Information Technologies, 28(1), 663–682. https://doi.org/10.1007/s10639-022-11194-2
   Web of Science ®Google Scholar
• Krings, H. P., & Koby, G. S. (2001). Repairing texts : Empirical investigations of machine translation post-editing processes. Kent State University Press.
   Google Scholar
• Lee, S.-M. (2020). The impact of using machine translation on EFL students’ writing. Computer Assisted Language Learning, 33(3), 157–175. https://doi.org/10.1080/09588221.2018.1553186
   Web of Science ®Google Scholar
• Lee, S.-M. (2021). The effectiveness of machine translation in foreign language education: A systematic review and meta-analysis. Computer Assisted Language Learning, 36(1–2), 1–23. https://doi.org/10.1080/09588221.2021.1901745
   Web of Science ®Google Scholar
• Li, X. (2015). International visibility of mainland China translation studies community: A scientometric study. Perspectives, 23(2), 183–204. https://doi.org/10.1080/0907676X.2015.1006645
   Web of Science ®Google Scholar
• Lim, M. H., & Aryadoust, V. (2021). A scientometric review of research trends in computer-assisted language learning (1977 – 2020). Computer Assisted Language Learning, 35(9), 2675–2700. https://doi.org/10.1080/09588221.2021.1892768
   Web of Science ®Google Scholar
• Mi, C., Xie, L., & Zhang, Y. (2022). Improving data augmentation for low resource speech-to-text translation with diverse paraphrasing. Neural Networks, 148, 194–205. https://doi.org/10.1016/j.neunet.2022.01.016
   PubMed Web of Science ®Google Scholar
• Mohsen, M. (2021). A bibliometric study of the applied linguistics research output of Saudi institutions in the Web of Science for the decade 2011-2020. The Electronic Library, 865–884. https://doi.org/10.1108/EL-06-2021-0121
   Google Scholar
• Mohsen, M. A., & Alangari, T. (2023). Analyzing two decades of immersive technology research in education: Trends, clusters, and future directions. Education and Information Technologies. https://doi.org/10.1007/s10639-023-11968-2
   Google Scholar
• Mohsen, M., & Ho, Y. (2022). Thirty years of educational research in Saudi Arabia: a bibliometric study. Interactive Learning Environments. https://doi.org/10.1080/10494820.2022.2127780
   Google Scholar
• Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences, 103(23), 8577–8582. https://doi.org/10.1073/pnas.0601602103
   PubMed Web of Science ®Google Scholar
• O’Brien, S. (2012). Translation as human–computer interaction. Translation Spaces, 1(1), 101–122. https://doi.org/10.1075/ts.1.05obr
   Google Scholar
• Papineni, K., Roukos, S., Ward, T., & Zhu, W.-J. (2002). BLEU: A method for automatic evaluation of machine translation Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, Philadelphia, Pennsylvania. https://doi.org/10.3115/1073083.1073135
   Google Scholar
• Plitt, M., & Masselot, F. (2010). A productivity test of statistical machine translation post-editing in a typical localisation context. The Prague Bulletin of Mathematical Linguistics, 93(1). https://doi.org/10.2478/v10108-010-0010-x
   Google Scholar
• Quah, C. K. (2006). Translation and technology. Springer. https://doi.org/10.1057/9780230287105
   Google Scholar
• Rivera-Trigueros, I. (2022). Machine translation systems and quality assessment: A systematic review. Language Resources and Evaluation, 56(2), 593–619. https://doi.org/10.1007/s10579-021-09537-5
   Web of Science ®Google Scholar
• Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53–65. https://doi.org/10.1016/0377-0427(87)90125-7
   Web of Science ®Google Scholar
• Rovira-Esteva, S., Orero, P., & Franco Aixelá, J. (2015). Bibliometric and bibliographical research in translation studies. Perspectives, 23(2), 159–160. https://doi.org/10.1080/0907676X.2015.1026361
   Web of Science ®Google Scholar
• Snover, M., Dorr, B., Schwartz, R., Micciulla, L., & Makhoul, J. (2006, August 8 12). A study of translation edit rate with targeted human annotation.Proceedings of the 7th Conference of the Association for Machine Translation in the Americas: Technical Papers Cambridge, Massachusetts, USA.
   Google Scholar
• Stahlschmidt, S., & Stephen, D. (2020). Comparison of Web of Science, Scopus and Dimensions data-bases. KB Forschungspoolprojekt; DZHW.
   Google Scholar
• Tan, Z., Wang, S., Yang, Z., Chen, G., Huang, X., Sun, M., & Liu, Y. (2020). Neural machine translation: A review of methods, resources, and tools. AI Open, 1, 5–21. https://doi.org/10.1016/j.aiopen.2020.11.001
   Google Scholar
• Van Doorslaer, L., & Gambier, Y. (2015). Measuring relationships in translation studies. On affiliations and keyword frequencies in the translation studies bibliography. Perspectives, 23(2), 305–319. https://doi.org/10.1080/0907676X.2015.1026360
   Web of Science ®Google Scholar
• van Eck, N. J., & Waltman, L. (2017). Citation-based clustering of publications using CitNetExplorer and VOSviewer. Scientometrics, 111(2), 1053–1070. https://doi.org/10.1007/s11192-017-2300-7
   PubMed Web of Science ®Google Scholar
• Vanroy, B. (2021). Syntactic difficulties in translation. Ghent University.
   Google Scholar
• Voß, S., & Zhao, X. (2005). Some steps towards a scientometric analysis of pub-lications in machine translation. Proceedings of the 23rd IASTED international multi-conference artificial intelligence and applications (pp. 651–655). Innsbruck, Austria.
   Google Scholar
• Wang, H., Wu, H., He, Z., Huang, L., & Church, K. W. (2021). Progress in machine translation. Engineering. https://doi.org/10.1016/j.eng.2021.03.023
   Web of Science ®Google Scholar
• Zhu, X., & Aryadoust, V. (2022). A scientometric review of research in translation studies in the twenty-first century. Target International Journal of Translation Studies, 35(2), 157–185. https://doi.org/10.1075/target.20154.zhu
   Web of Science ®Google Scholar