Bold ideas and critical thoughts on science.

Martin Schmidt, Benedikt Fecher, Christian Kobsda

11000111 authors

Bibliometrics for the subject areas Computer Science and Decision Sciences for the 20 highest performing authors.
3 August 2017

Description

The number of authors per article in the subject area Computer Science is 4 on average with a maximum of 21 authors. The mean number of coauthors is increasing by 0.1 per year in the respective time period (Figure 1). The articles in this analysis (n = 1558) were cited 11.4 times on average with a maximum of 199 citations.

Figure 1: Boxplot of the number of authors per paper in the subject area Computer Science. The box denotes 25–75% of the values with the median (bold line) in it. The small circles are outliers. Due to a limitation of the y-axis, some outliers are not shown. The yellow line shows a linear model of the mean number of authors per article with a confidence interval of 0.95 shown in light grey. Data source: Scopus. CC BY 4.0 Schmidt, Fecher, Kobsda.

The number of authors per article in the subject area Decision Sciences is 3.1 on average with a maximum of 13 authors (Figure 2). The mean number of coauthors is decreasing by 0.02 per year in the respective time period. The articles in this analysis (n = 192) were cited 7 times on average and 35 as maximum which is the smallest number.

Figure 2: Boxplot of the number of authors per paper in the subject area Decision Sciences. The box denotes 25–75% of the values with the median (bold line) in it. The small circles are outliers. Due to a limitation of the y-axis, some outliers are not shown. The yellow line shows a linear model of the mean number of authors per article with a confidence interval of 0.95 shown in light grey. Data source: Scopus. CC BY 4.0 Schmidt, Fecher, Kobsda.

Methodology

The results of the Advanced search in Scopus were restricted by an algorithm with

  • a time period of publishing (2010 to 2016)
  • the document types (articles or reviews),
  • and a quantitative limitation regarding the publication output (articles by the 20 highest performing authors with the most Scopus listed articles in every subject area).

For details and code see Schmidt et al. 2017.

Author info

Martin Schmidt is a doctoral researcher at the Institute of Landscape Systems Analysis within Leibniz Centre for Agricultural Landscape Research and associate researcher at Alexander von Humboldt Institute for Internet and Society.

Benedikt Fecher is the programme director of the research programme Knowledge Dimension and heads the Open Science research group at the Alexander von Humboldt Institute for Internet and Society.

Christian Kobsda works as the political consultant at the Leibniz Association and is an associate researcher at the Alexander von Humboldt Institute for Internet and Society.

Digital Object Identifier (DOI)

https://doi.org/10.5281/zenodo.834677

Cite as

Schmidt, M., Fecher, B., Kobsda, C. (2017). Bibliometrics for the Subject Areas Computer Science and Decision Sciences for the 20 Highest Performing Authors. Elephant in the lab. DOI: 10.5281/zenodo.834677

References

Collapse references

Schmidt, M., Fecher, B., Kobsda, C. (2017). Methodology for the analysis of authors using meta data from Scopus. Elephant in the Labhttps://doi.org/10.5281/zenodo.805718

0 Comments

Continue reading

Power and Publications in Chinese Academia

Power and Publications in Chinese Academia

Ruixue Jia on the influence of administrative power in Chinese academia on researchers’ publication activity, their selection of co-authors, and the topics they are writing about.