Reconsidering the gold open access citation advantage postulate in a multidisciplinary context: an analysis of the subject categories in the Web of Science database 2009-2014

Authors : Pablo Dorta-González,  Sara M. González-Betancor, María Isabel Dorta-González

Since Lawrence in 2001 proposed the open access (OA) citation advantage, the potential benefit of OA in relation to the citation impact has been discussed in depth.

The methodology to test this postulate ranges from comparing the impact factors of OA journals versus traditional ones, to comparing citations of OA versus non-OA articles published in the same non-OA journals.

However, conclusions are not entirely consistent among fields, and two possible explications have been suggested in those fields where a citation advantage has been observed for OA: the early view and the selection bias postulates.

In this study, a longitudinal and multidisciplinary analysis of the gold OA citation advantage is developed. All research articles in all journals for all subject categories in the multidisciplinary database Web of Science are considered.

A total of 1,137,634 articles – 86,712 OA articles (7.6%) and 1,050,922 non-OA articles (92.4%)- published in 2009 are analysed. The citation window considered goes from 2009 to 2014, and data are aggregated for the 249 disciplines (subject categories).

At journal level, we also study the evolution of journal impact factors for OA and non-OA journals in those disciplines whose OA prevalence is higher (top 36 subject categories). As the main conclusion, there is no generalizable gold OA citation advantage, neither at article nor at journal level.


A Framework to Explore the Knowledge Structure of Multidisciplinary Research Fields

Understanding emerging areas of a multidisciplinary research field is crucial for researchers, policymakers and other stakeholders. For them a knowledge structure based on longitudinal bibliographic data can be an effective instrument. But with the vast amount of available online information it is often hard to understand the knowledge structure for data.

In this paper, we present a novel approach for retrieving online bibliographic data and propose a framework for exploring knowledge structure. We also present several longitudinal analyses to interpret and visualize the last 20 years of published obesity research data.

URL : A Framework to Explore the Knowledge Structure of Multidisciplinary Research Fields


The Zen of Multidisciplinary Team Recommendation

« In order to accomplish complex tasks, it is often necessary to compose a team consisting of experts with diverse competencies. However, for proper functioning, it is also preferable that a team be socially cohesive. A team recommendation system, which facilitates the search for potential team members can be of great help both for (i) individuals who need to seek out collaborators and (ii) managers who need to build a team for some specific tasks.
A decision support system which readily helps summarize such metrics, and possibly rank the teams in a personalized manner according to the end users’ preferences, can be a great tool to navigate what would otherwise be an information avalanche.
In this work we present a general framework of how to compose such subsystems together to build a composite team recommendation system, and instantiate it for a case study of academic teams. »