Google Scholar as a data source for research assessment

Authors : Emilio Delgado López-Cózar, Enrique Orduna-Malea, Alberto Martín-Martín

The launch of Google Scholar (GS) marked the beginning of a revolution in the scientific information market. This search engine, unlike traditional databases, automatically indexes information from the academic web. Its ease of use, together with its wide coverage and fast indexing speed, have made it the first tool most scientists currently turn to when they need to carry out a literature search.

Additionally, the fact that its search results were accompanied from the beginning by citation counts, as well as the later development of secondary products which leverage this citation data (such as Google Scholar Metrics and Google Scholar Citations), made many scientists wonder about its potential as a source of data for bibliometric analyses.

The goal of this chapter is to lay the foundations for the use of GS as a supplementary source (and in some disciplines, arguably the best alternative) for scientific evaluation.

First, we present a general overview of how GS works. Second, we present empirical evidences about its main characteristics (size, coverage, and growth rate). Third, we carry out a systematic analysis of the main limitations this search engine presents as a tool for the evaluation of scientific performance.

Lastly, we discuss the main differences between GS and other more traditional bibliographic databases in light of the correlations found between their citation data. We conclude that Google Scholar presents a broader view of the academic world because it has brought to light a great amount of sources that were not previously visible.

URL : https://arxiv.org/abs/1806.04435

A citation analysis of top research papers of…

A citation analysis of top research papers of computer science :

« The study intends to evaluate the top papers of Computer Science as reflected in Science Direct. Moreover, it aims to find out authorship pattern, ranking of authors, ranking of country productivity, ranking of journals, and highly cited papers of Computer Science. The citations data have been collected from the quarterly list of hottest 25 research articles in the subject field of Computer Science from Science Direct database. In the present study, 20 issues of the alert service beginning from January/March 2005 to October/December 2010 containing a total number of 495 articles in Computer Science have been taken up for analysis. The study reveals that out of 495 top papers; three-authored articles are little ahead than two authored articles followed by four-authored articles and the country productivity of USA is at the top followed by UK, Taiwan, Chaina, and Canada. Moreover, it finds that European Journal of Operational Research occupies the top position followed by Computers in Human Behavior, and Pattern Recognition. »

URL : http://hdl.handle.net/10760/16859