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Bibliometric analysis and visualization of translation assessment: Research theme, evolution and hotspots

Dai Tao, Lin Siew Eng

Article ID: 2135
Vol 6, Issue 2, 2024, Article identifier:

VIEWS - 528 (Abstract) 303 (PDF)

Abstract

Translation assessment, referring to evaluating various aspects related to translation, is crucial to the improvement of translation competence and quality. This study, taking valid papers on translation assessment published in WoS core collection from 2000 to 2022 as research samples, visualizes and reviews the research theme, research evolutions and emerging hot topics of translation assessment through bibliometric analysis. The number of annual publications shows that despite the general growth, the number of articles on translation assessment fluctuates from year to year. By Cite Space-based analysis of keywords co-occurrence, keyword clustering, time zone and burst detection, it finds that translation assessment mainly covers five themes, namely translation competence, translation quality, machine translation, translation teaching and training, and others. The overall evolution has been a gradual shift from concepts, metrics and evaluations of topics related to translation assessment into a topic of in-depth and interdisciplinary study. The hotspots in recent years include translation competence acquisition, neural machine translation and translation quality estimation. The findings reveal research evolutions and hot spots, propose implications for further translation assessment research and provide references for scholars who are interested in this topic.


Keywords

translation assessment; translation competence; translation quality; bibliometrics analysis

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DOI: https://doi.org/10.59400/fls.v6i2.2135
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