Tren Penelitian Penerjemahan Teks Bahasa Arab Berbasis Artificial Intelligence: Kajian Bibliometrik - Abdul Aziz, Riza Abdul Aziz; Sopian, Asep; Supriadi, Rinaldi (Uktub (Online), 2025)
This study examines trends in Arabic text translation research based on Artificial Intelligence (AI) through a bibliometric approach using visual mapping analysis with the VOSviewer software. Data were obtained from the Scopus database using the Publish or Perish application, employing the keywords “arabic AND translation AND artificial AND intelligence” for the period from 2014 to 2024. A total of 70 relevant documents were identified and analyzed to observe publication trends, citation patterns, as well as networks of scientific and thematic collaboration. The findings show that research trends have increased significantly, particularly in 2024, which saw 25 publications. Bibliometric visualization identified six main clusters in the keyword network, including machine translation, deep learning, computational linguistics, and Arabic sign language. The term “Artificial Intelligence” was central to the entire network. Overlay analysis revealed that topics such as “ChatGPT” and “quality control” have emerged as recent growing issues. Research collaboration spans 29 countries, with Saudi Arabia and the United States as central hubs in the collaboration network. This study underscores that research on Arabic text translation based on AI is growing rapidly and is multidisciplinary in nature. The findings make a significant contribution to mapping the scientific landscape and highlight wide-open opportunities for future research in the field of Arabic computational linguistics. These findings provide a substantial contribution to strengthening the scientific foundation of AI-based translation and serve as a strategic reference for researchers and policymakers in developing new research directions aligned with the demands of the digital era and the advancement of Arabic language technology.