paper

Bibliometric author evaluation through linear regression on the coauthor network

arXiv:1504.03115 · doi:10.1016/j.joi.2017.01.003

Abstract

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.

13 pages, 2 figures

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