Google Scholar: the 'big data' bibliographic tool

TL;DR

Google Scholar revolutionized academic search with its extensive coverage and ease of use, but has limitations as a bibliometric tool, prompting the development of various metrics and software for research evaluation.

Contribution

This paper analyzes how Google Scholar operates and explores its potential and limitations for bibliometric research and evaluation.

Findings

Google Scholar offers unparalleled coverage of academic documents.

Several bibliometric tools and metrics have been developed based on Google Scholar data.

Google Scholar's uncontrolled indexing presents both opportunities and challenges for research evaluation.

Abstract

The launch of Google Scholar back in 2004 meant a revolution not only in the scientific information search market but also in research evaluation processes. Its dynamism, unparalleled coverage, and uncontrolled indexing make of Google Scholar an unusual product, especially when compared to traditional bibliographic databases. Conceived primarily as a discovery tool for academic information, it presents a number of limitations as a bibliometric tool. The main objective of this chapter is to show how Google Scholar operates and how its core database may be used for bibliometric purposes. To do this, the general features of the search engine (in terms of document typologies, disciplines, and coverage) are analysed. Lastly, several bibliometric tools based on Google Scholar data, both official (Google Scholar Metrics, Google Scholar Citations), and some developed by third parties (H Index Scholar, Publishers Scholar Metrics, Proceedings Scholar Metrics, Journal Scholar Metrics, Scholar Mirrors), as well as software to collect and process data from this source (Publish or Perish, Scholarometer) are introduced, aiming to illustrate the potential bibliometric uses of this source.