Analysis on MathSciNet database: some preliminary results
Serge Richard, Qiwen Sun
TL;DR
This paper explores the MathSciNet database to analyze the impact of international collaborations on citation counts in mathematics, providing initial insights and establishing a foundation for further research.
Contribution
It offers the first independent investigation and statistical analysis of MathSciNet data related to international collaborations and citations in mathematics.
Findings
International collaborations may increase citation counts
MathSciNet can be used for statistical analysis in mathematics research
Preliminary results suggest patterns worth further exploration
Abstract
In this paper we initiate some investigations on MathSciNet database. For many mathematicians this website is used on a regular basis, but surprisingly except for the information provided by MathSciNet itself, there exist almost no independent investigations or independent statistics on this database. This current research has been triggered by a rumor: do international collaborations increase the number of citations of an academic work in mathematics? We use MathSciNet for providing some information about this rumor, and more generally pave the way for further investigations on or with MathSciNet. Keywords: MathSciNet, tree-based methods, international collaborations
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Taxonomy
TopicsData Mining Algorithms and Applications · Machine Learning and Data Classification · Data Stream Mining Techniques