Empirical Patterns in Google Scholar Citation Counts

Abstract

Scholarly impact can be measured crudely by the number of citations as a approximate indication of impact in terms of influencing other researchers, but this metric varies in applicability between disciplines. The number of citations for each publication of an author can be mapped as a graph in various ways. In doing so, certain empirical patterns may be discerned. This paper explores these patterns, using citation data from Google Scholar for a number of authors.