A Comparative Analysis of Domestic and International Research on Machine Translation Based on CiteSpace
Year: 2025
Type: conference-paper
Abstract: This thesis takes relevant literature from 1998 to 2025 in the CNKI and Web of Science databases as its research objects, adopts bibliometric methods, and uses the CiteSpace software to generate a knowledge map of “machine translation” research. The thesis analyzes the research trends, leading research institutions, and research hotspots as visualized in the knowledge map. Comparative analysis shows that the research hotspots and development trends in the field of machine translation at home and abroad are highly similar, with a main focus on neural machine translation and artificial intelligence. However, there is a gap in the degree of research attention, and there is still considerable room for growth in China's research on machine translation.
Authors: Qianqian Peng, Aihua Yang
Institution: National University of Defense Technology
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: gold
OpenAlex ID: W4414931890