The current study aims to map the scientific output of grey literature (GL) through bibliometric approaches.
The source for data extraction is a comprehensive “indexing and abstracting” database, “Web of Science” (WOS). A lexical title search was applied to get the corpus of the study – a total of 4,599 articles were extracted for data analysis and visualisation. Further, the data were analysed by using the data analytical tools, R-studio and VOSViewer.
The findings showed that the “publications” have substantially grown up during the timeline. The most productive phase (2018–2021) resulted in 47% of articles. The prominent sources were PLOS One and NeuroImage. The highest number of papers were contributed by Haddaway and Kumar. The most relevant countries were the USA and UK.
The study is useful for researchers interested in the GL research domain. The study helps to understand the evolution of the GL to provide research support further in this area.
The present study provides a new orientation to the scholarly output of the GL. The study is rigorous and all-inclusive based on analytical operations like the research networks, collaboration and visualisation. To the best of the authors' knowledge, this manuscript is original, and no similar works have been found with the research objectives included here.
Wani, J.A. and Ganaie, S.A. (2022), "The scientific outcome in the domain of grey literature: bibliometric mapping and visualisation using the R-bibliometrix package and the VOSviewer", Library Hi Tech, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/LHT-01-2022-0012
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