Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns
Abstract 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, suc...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2023-05-01
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| Series: | Journal of Big Data |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40537-023-00744-1 |
| _version_ | 1797822830488846336 |
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| author | Irena Mitrović Marko Mišić Jelica Protić |
| author_facet | Irena Mitrović Marko Mišić Jelica Protić |
| author_sort | Irena Mitrović |
| collection | DOAJ |
| description | Abstract 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. |
| first_indexed | 2024-03-13T10:15:03Z |
| format | Article |
| id | doaj.art-c73c68e6a4614aaf84ee74d63e190642 |
| institution | Directory Open Access Journal |
| issn | 2196-1115 |
| language | English |
| last_indexed | 2024-03-13T10:15:03Z |
| publishDate | 2023-05-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of Big Data |
| spelling | doaj.art-c73c68e6a4614aaf84ee74d63e1906422023-05-21T11:18:36ZengSpringerOpenJournal of Big Data2196-11152023-05-0110112810.1186/s40537-023-00744-1Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patternsIrena Mitrović0Marko Mišić1Jelica Protić2School of Electrical Engineering, University of BelgradeSchool of Electrical Engineering, University of BelgradeSchool of Electrical Engineering, University of BelgradeAbstract 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.https://doi.org/10.1186/s40537-023-00744-1Data mining and analysisCo-authorship networks analysisCollaborative behaviorResearch evaluationScientometrics |
| spellingShingle | Irena Mitrović Marko Mišić Jelica Protić Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns Journal of Big Data Data mining and analysis Co-authorship networks analysis Collaborative behavior Research evaluation Scientometrics |
| title | Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns |
| title_full | Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns |
| title_fullStr | Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns |
| title_full_unstemmed | Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns |
| title_short | Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns |
| title_sort | exploring high scientific productivity in international co authorship of a small developing country based on collaboration patterns |
| topic | Data mining and analysis Co-authorship networks analysis Collaborative behavior Research evaluation Scientometrics |
| url | https://doi.org/10.1186/s40537-023-00744-1 |
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