Bibliometric author evaluation through linear regression on the coauthor network

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. (C) 2017 Elsevier Ltd. All rights reserved.