
Abstract Recently, there is a growing interest in the development of translation quality research programmes at different stages worldwide. Scholars and researchers have paid much attention to the quality of translation; however, there is a dearth of meta-analyses of studies and research in the field of translation quality research. In fact there has been no systematic review since 2000. The purpose of the current research paper is to design translation quality research through the construction of a database of 14 peer-reviewed journal publications during the period 2000 to 2017. A combination of thematic and methodological analyses, scientometric methods, and corpus tool were applied to analyse the extracted database. Also, top-down and bottom-up procedures were conducted to minimise the subjectivity of thematic analysis. The present research scrutinised the extracted database on the basis of four main criteria, namely theoretical importance, pertinence to empirical and non-empirical research, the size of readership, and geographical coverage including institutions and countries. Finally, this database aims at serving as a resource for researchers and scholars to become familiar with the most cutting edge information on developments in translation quality research, challenges within this field, and the possible trajectories for future research.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
