Evidence of Open Access of scientific publications in Google Scholar: a large-scale analysis

Authors : Alberto Martín-Martín, Rodrigo Costas, Thed van Leeuwen, Emilio López-Cózar

This article uses Google Scholar (GS) as a source of data to analyse Open Access (OA) levels across all countries and fields of research. All articles and reviews with a DOI and published in 2009 or 2014 and covered by the three main citation indexes in the Web of Science (2,269,022 documents) were selected for study.

The links to freely available versions of these documents displayed in GS were collected. To differentiate between more reliable (sustainable and legal) forms of access and less reliable ones, the data extracted from GS was combined with information available in DOAJ, CrossRef, OpenDOAR, and ROAR.

This allowed us to distinguish the percentage of documents in our sample that are made OA by the publisher (23.1%, including Gold, Hybrid, Delayed, and Bronze OA) from those available as Green OA (17.6%), and those available from other sources (40.6%, mainly due to ResearchGate).

The data shows an overall free availability of 54.6%, with important differences at the country and subject category levels. The data extracted from GS yielded very similar results to those found by other studies that analysed similar samples of documents, but employed different methods to find evidence of OA, thus suggesting a relative consistency among methods.

URL : Evidence of Open Access of scientific publications in Google Scholar: a large-scale analysis

Alternative location : https://osf.io/preprints/socarxiv/k54uv/

The counting house: measuring those who count. Presence of Bibliometrics, Scientometrics, Informetrics, Webometrics and Altmetrics in the Google Scholar Citations, ResearcherID, ResearchGate, Mendeley & Twitter

Authors : Alberto Martin-Martin, Enrique Orduna-Malea, Juan M. Ayllon, Emilio Delgado Lopez-Cozar

Following in the footsteps of the model of scientific communication, which has recently gone through a metamorphosis (from the Gutenberg galaxy to the Web galaxy), a change in the model and methods of scientific evaluation is also taking place.

A set of new scientific tools are now providing a variety of indicators which measure all actions and interactions among scientists in the digital space, making new aspects of scientific communication emerge.

In this work we present a method for capturing the structure of an entire scientific community (the Bibliometrics, Scientometrics, Informetrics, Webometrics, and Altmetrics community) and the main agents that are part of it (scientists, documents, and sources) through the lens of Google Scholar Citations.

Additionally, we compare these author portraits to the ones offered by other profile or social platforms currently used by academics (ResearcherID, ResearchGate, Mendeley, and Twitter), in order to test their degree of use, completeness, reliability, and the validity of the information they provide.

A sample of 814 authors (researchers in Bibliometrics with a public profile created in Google Scholar Citations was subsequently searched in the other platforms, collecting the main indicators computed by each of them.

The data collection was carried out on September, 2015. The Spearman correlation was applied to these indicators (a total of 31) , and a Principal Component Analysis was carried out in order to reveal the relationships among metrics and platforms as well as the possible existence of metric cluster.

URL : https://arxiv.org/abs/1602.02412