Google Scholar: The big data bibliographic tool

Delgado López-Cózar, E. Orduña-Malea, E.,  Martín-Martín, A.,  Ayllón, J.M. (2017). 
Google Scholar: The big data bibliographic tool. 
In: Cantu-Ortiz, FJ. (ed.). Research Analytics: Boosting University Productivity and Competitiveness through Scientometrics. 
CRC Press (Taylor & Francis Group), 2017 p. 59-80 
goo.gl/vvPf7g 

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 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 analyzed. 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.