Machine Translation Quality Evaluation Research Landscape: A Bibliometric Analysis

This study conducts a bibliometric analysis of literature on machine translation quality evaluation from the Web of Science Core Collection between 2000 and 2025 using visualization tools CiteSpace and VOSviewer, aiming to elucidate the current landscape, research hotspots, and emerging trends in international machine translation quality evaluation. The findings reveal that recent research in this field demonstrates a fluctuating upward trajectory with steady progress within an overall stable development pattern, characterized by a dual emphasis on collaborative teamwork and independent research within the academic community. Current research hotspots predominantly concentrate on automated evaluation methods, data models, and evaluation metrics. Future research is anticipated to focus on domain-specific adaptation and the refinement of evaluation metrics.