4.5 Article

Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns

期刊

JOURNAL OF BIG DATA
卷 10, 期 1, 页码 -

出版社

SPRINGERNATURE
DOI: 10.1186/s40537-023-00744-1

关键词

Data mining and analysis; Co-authorship networks analysis; Collaborative behavior; Research evaluation; Scientometrics

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The number of scientific papers published each year is rapidly increasing, exceeding 2.9 million annually. New methodologies and systems have been developed to analyze the vast amount of data available from scientific databases such as Web of Science or Scopus. This paper analyzes the international scientific production and co-authorship patterns of the most productive authors from Serbia, based on the Web of Science dataset from 2006 to 2013. The authors conducted bibliometric and scientometric analyses, as well as statistical and collaboration network analysis, to understand the reasons behind the exceptional publishing performance of certain authors.
The number of published scientific paper grows rapidly each year, totaling more than 2.9 million annually. New methodologies and systems have been developed to analyze scientific production and performance indicators from large quantities of data available from the scientific databases, such as Web of Science or Scopus. In this paper, we analyzed the international scientific production and co-authorship patterns for the most productive authors from Serbia based on the obtained Web of Science dataset in the period 2006-2013. We performed bibliometric and scientometric analyses together with statistical and collaboration network analysis, to reveal the causes of extraordinary publishing performance of some authors. For such authors, we found significant inequality in distribution of papers over journals and countries of co-authors, using Gini coefficient and Lorenz curves. Most of the papers belong to multidisciplinary, interdisciplinary, and the field of applied sciences. We have discovered three specific collaboration patterns that lead to high productivity in international collaboration. First pattern corresponds to mega-authorship papers with hundreds of co-authors gathered in specific research groups. The other two collaboration patterns were found in mathematics and multidisciplinary science, mainly application of graph theory and computational methods in physical chemistry. The former pattern results in a star-shaped collaboration network with mostly individual collaborators. The latter pattern includes multiple actors with high betweenness centrality measure and identified brokerage roles. The results are compared with the later period 2014-2023, where high scientific production has been observed in some other fields, such as biology and food science and technology.

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