TechMiner: Analysis of bibliographic datasets using Python

Bibliometric analyses and tech-mining studies are assuming a crucial role in research, covering the need to synthetize current knowledge; however, they can be difficult to conduct due to several analyses employ different software tools, some of them available only under commercial licenses, and in s...

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Bibliographic Details
Published inSoftwareX Vol. 23; p. 101457
Main Author Velasquez, Juan D.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.07.2023
Elsevier
Subjects
Bibliometrics
Science mapping
Systematic literature review
Systematic mapping study
Tech-mining studies
Science mapping
Tech-mining studies
Bibliometrics
Systematic mapping study
Systematic literature review
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Summary:Bibliometric analyses and tech-mining studies are assuming a crucial role in research, covering the need to synthetize current knowledge; however, they can be difficult to conduct due to several analyses employ different software tools, some of them available only under commercial licenses, and in some cases, requiring advanced programming skills for their use. This article introduces a graphical Python-based application that performs bibliometric and statistical analyses of data sets extracted from Scopus. TechMiner allows the user to run basic task as data cleaning and author disambiguation and advanced analyses as keyword clustering or citation analysis.
ISSN:2352-7110
2352-7110
DOI:10.1016/j.softx.2023.101457