Empirical Patterns in Google Scholar Citation Counts

Abstract

Abstract—Scholarly impact may be metricized using an au-thor’s total number of citations as a stand-in for real worth, but this measure varies in applicability between disciplines. The detail of the number of citations per publication is nowadays mapped in much more detail on the Web, exposing certain empirical patterns. This paper explores those patterns, using the citation data from Google Scholar for a number of authors. I. BACKGROUND The speed of transmission and the quantity of knowledge available to researchers has accelerated dramatically in recent decades with the advent of the Internet and the World Wide Web. Whereas, previously, academic papers were really pub-lished only on paper, in journals and books, now they can be and often are communicated ‘online’. That has led to this body of information on academic activity becoming ever more comprehensively indexed. Google, as well as ubiquitously indexing all of the Web, provides an index of academic publications in particular through its Google Scholar website

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No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 27 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.