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1 – 1 of 1Javaid Ahmad Wani, Ikhlaq Ur Rehman, Shabir Ahmad Ganaie and Aasia Maqbool
This study aims to measure scientific literature on the emerging research area of “big data” in the field of “library and information science” (LIS).
Abstract
Purpose
This study aims to measure scientific literature on the emerging research area of “big data” in the field of “library and information science” (LIS).
Design/methodology/approach
This study used the “bibliometric method” for data curation. Web of Science and altmetric.com were used. Data analysis and visualisation were done using three widely used powerful data analytics software, R-bibliometrix, VOSviewer and Statistical Package for Social Sciences.
Findings
This study revealed the most preferred venues for publication. Furthermore, this study highlighted an association between the Mendeley readers of publications and citations. Furthermore, it was evident that the overall altimetric attention score (AAS) does not influence the citation score of publications. Other fascinating findings were moderate collaboration patterns overall. Furthermore, the study highlighted that big data (BD) research output and scientific influence in the LIS sector are continually increasing.
Practical implications
Findings related to BD analytics in LIS techniques can serve as helpful information for researchers, practitioners and policymakers.
Originality/value
This study contributes to the current knowledge accumulation by its unique manner of blending the two approaches, bibliometrics and altmetrics.
Details