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/
Authors : Thed van Leeuwen, Ingeborg Meijer, Alfredo Yegros-Yegros, Rodrigo Costas
In the last couple of years, the role of Open Access (OA) publishing has become central in science management and research policy. In the UK and the Netherlands, national OA mandates require the scientific community to seriously consider publishing research outputs in OA forms.
At the same time, other elements of Open Science are becoming also part of the debate, thus including not only publishing research outputs but also other related aspects of the chain of scientific knowledge production such as open peer review and open data.
From a research management point of view, it is important to keep track of the progress made in the OA publishing debate. Until now, this has been quite problematic, given the fact that OA as a topic is hard to grasp by bibliometric methods, as most databases supporting bibliometric data lack exhaustive and accurate open access labelling of scientific publications.
In this study, we present a methodology that systematically creates OA labels for large sets of publications processed in the Web of Science database. The methodology is based on the combination of diverse data sources that provide evidence of publications being OA.
URL : https://arxiv.org/abs/1802.02827v1
Authors : Rodrigo Costas, Jeroen van Honk, Thomas Franssen
In this paper we present a novel methodology for identifying scholars with a Twitter account. By combining bibliometric data from Web of Science and Twitter users identified by Altmetric.com we have obtained the largest set of individual scholars matched with Twitter users made so far.
Our methodology consists of a combination of matching algorithms, considering different linguistic elements of both author names and Twitter names; followed by a rule-based scoring system that weights the common occurrence of several elements related with the names, individual elements and activities of both Twitter users and scholars matched.
Our results indicate that about 2% of the overall population of scholars in the Web of Science is active on Twitter. By domain we find a strong presence of researchers from the Social Sciences and the Humanities. Natural Sciences is the domain with the lowest level of scholars on Twitter.
Researchers on Twitter also tend to be younger than those that are not on Twitter. As this is a bibliometric-based approach, it is important to highlight the reliance of the method on the number of publications produced and tweeted by the scholars, thus the share of scholars on Twitter ranges between 1% and 5% depending on their level of productivity. Further research is suggested in order to improve and expand the methodology.
URL : https://arxiv.org/abs/1712.05667
Authors : Nicolas Robinson-Garcia, Rodrigo Costas, Kimberley Isett, Julia Melkers, Diana Hicks
Enthusiasm for using Twitter as a source of data in the social sciences extends to measuring the impact of research with Twitter data being a key component in the new altmetrics approach. In this paper, we examine tweets containing links to research articles in the field of dentistry to assess the extent to which tweeting about scientific papers signifies engagement with, attention to, or consumption of scientific literature.
The main goal is to better comprehend the role Twitter plays in scholarly communication and the potential value of tweet counts as traces of broader engagement with scientific literature. In particular, the pattern of tweeting to the top ten most tweeted scientific dental articles and of tweeting by accounts is examined.
The ideal that tweeting about scholarly articles represents curating and informing about state-of-the-art appears not to be realized in practice. We see much presumably human tweeting almost entirely mechanical and devoid of original thought, no evidence of conversation, tweets generated by monomania, duplicate tweeting from many accounts under centralized professional management and tweets generated by bots.
Some accounts exemplify the ideal, but they represent less than 10% of tweets. Therefore, any conclusions drawn from twitter data is swamped by the mechanical nature of the bulk of tweeting behavior. In light of these results, we discuss the compatibility of Twitter with the research enterprise as well as some of the financial incentives behind these patterns.
URL : The unbearable emptiness of tweeting — About journal articles
DOI : https://doi.org/10.1371/journal.pone.0183551