Do mathematicians, economists and biomedical scientists trace large topics more strongly than physicists?

Menghui Li, Liying Yang, Huina Zhang, Zhesi Shen, Chensheng Wu and Jinshan Wu

Journal of Informetrics, 2017, vol. 11, issue 2, 598-607

Abstract: In this work, we extend our previous work on largeness tracing among physicists to other fields, namely mathematics, economics and biomedical science. Overall, the results confirm our previous discovery, indicating that scientists in all these fields trace large topics. Surprisingly, however, it seems that researchers in mathematics tend to be more likely to trace large topics than those in the other fields. We also find that on average, papers in top journals are less largeness-driven. We compare researchers from the USA, Germany, Japan and China and find that Chinese researchers exhibit consistently larger exponents, indicating that in all these fields, Chinese researchers trace large topics more strongly than others. Further correlation analyses between the degree of largeness tracing and the numbers of authors, affiliations and references per paper reveal positive correlations – papers with more authors, affiliations or references are likely to be more largeness-driven, with several interesting and noteworthy exceptions: in economics, papers with more references are not necessary more largeness-driven, and the same is true for papers with more authors in biomedical science. We believe that these empirical discoveries may be valuable to science policy-makers.

Keywords: Research choice; Matthew effect; Large topics (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:11:y:2017:i:2:p:598-607

DOI: 10.1016/j.joi.2017.04.004

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