EPJ Data Science (Mar 2018)

Feature analysis of multidisciplinary scientific collaboration patterns based on PNAS

  • Zheng Xie,
  • Miao Li,
  • Jianping Li,
  • Xiaojun Duan,
  • Zhenzheng Ouyang

DOI
https://doi.org/10.1140/epjds/s13688-018-0134-z
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 17

Abstract

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Abstract The features of collaboration patterns are often considered to be different from discipline to discipline. Meanwhile, collaborating among disciplines is an obvious feature emerged in modern scientific research, which incubates several interdisciplines. The features of collaborations in and among the disciplines of biological, physical and social sciences are analyzed based on 52,803 papers published in a multidisciplinary journal PNAS during 1999 to 2013. From those data, we found similar transitivity and assortativity of collaboration patterns as well as the identical distribution type of collaborators per author and that of papers per author, namely a mixture of generalized Poisson and power-law distributions. In addition, we found that interdisciplinary research is undertaken by a considerable fraction of authors, not just those with many collaborators or those with many papers. This case study provides a window for understanding aspects of multidisciplinary and interdisciplinary collaboration patterns.

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