Bibliometric author evaluation through linear regression on the coauthor network
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Abstract (arXiv)
The rising trend of coauthored academic works obscures the credit assignment that is the basis for decisions of funding and career advancements. In this paper, a simple model based on the assumption of an unvarying "author ability" is introduced. With this assumption, the weight of author contributions to a body of coauthored work can be statistically estimated. The method is tested on a set of some more than five-hundred authors in a coauthor network from the CiteSeerX database. The ranking obtained agrees fairly well with that given by total fractional citation counts for an author, but noticeable differences exist.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). First posted on arXiv 13 Apr 2015.
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