Scientometrics

, Volume 114, Issue 2, pp 463–479 | Cite as

Measuring the stability of scientific collaboration

  • Yi Bu
  • Dakota S. Murray
  • Ying Ding
  • Yong Huang
  • Yiming Zhao
Article

Abstract

Stability has long been regarded as an important characteristic of many natural and social processes. In regards to scientific collaborations, we define stability to reflect the consistent investment of a certain amount of effort into a relationship. In this paper, we provide an explicit definition of a new indicator of stability, based on the year-to-year publication output of collaborations. We conduct a large-scale analysis of stability among collaborations between authors publishing in the field of computer science. Collaborations with medium–high degree of stability tend to occur most frequently, and on average, have the highest average scientific impact. We explore other “circumstances”, reflecting the composition of collaborators, that may interact with the relationship between stability and impact, and show that (1) Transdisciplinary collaborations with low stability leads to high impact publications; (2) Stable collaboration with the collaborative author pairs showing greater difference in scientific age or career impact can produce high impact publications; and (3) Highly-cited collaborators whose publications have a large number of co-authors do not keep stable collaborations. We also demonstrate how our indicator for stability can be used alongside other similar indicators, such as persistence, to better understand the nature of scientific collaboration, and outline a new taxonomy of collaborations.

Keywords

Scientific collaboration Stability Persistence Scientometrics 

Mathematics Subject Classification

62P25 

JEL Classification

O35 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Numbers: 71420107026 and 71403190).

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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2017

Authors and Affiliations

  • Yi Bu
    • 1
  • Dakota S. Murray
    • 1
  • Ying Ding
    • 1
    • 2
  • Yong Huang
    • 2
  • Yiming Zhao
    • 3
  1. 1.School of Informatics, Computing, and EngineeringIndiana UniversityBloomingtonUSA
  2. 2.School of Information ManagementWuhan UniversityWuhanChina
  3. 3.Center for Studies of Information ResourcesWuhan UniversityWuhanChina

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