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Solving the cold-start problem in scientific credit allocation

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  • Xing, Yanmeng
  • Wang, Fenghua
  • Zeng, An
  • Ying, Fan

Abstract

A nearly universal trend in science today is the prominence of ever-increasing collaborative teams. Hence, identifying the relative credit due to each collaborator of published studies is of high significance. Although numerous methods have been employed to address this issue, allocating credit to all co-authors of new papers remains challenging. To address this cold-start issue, we introduce a credit allocation algorithm based on the co-citing network that captures the co-authors’ shared credit of a multi-authored publication. Using the American Physical Society publication data, we validate the method by examining papers by Nobel laureates. Accordingly, we perform many experiments to demonstrate that the proposed method can be implemented on academic papers in any period after publication with a significantly higher degree of accuracy and robustness than the existing algorithms applied to new papers. This method enables us to explore the universal credit evolution pattern of scientific elites. Importantly, by testing the relation between an author's credit and authorship byline, we observe that the first authors of papers are currently assigned less credit than in the early days with respect to physics. With collaboration and a large team set to dominate the agenda of the current science system, our study provides a more effective method for allocating early credit to co-authors of a paper, which may be beneficial to various academic activities, including faculty hiring, funding, and promotion decisions.

Suggested Citation

  • Xing, Yanmeng & Wang, Fenghua & Zeng, An & Ying, Fan, 2021. "Solving the cold-start problem in scientific credit allocation," Journal of Informetrics, Elsevier, vol. 15(3).
  • Handle: RePEc:eee:infome:v:15:y:2021:i:3:s1751157721000286
    DOI: 10.1016/j.joi.2021.101157
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