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Evaluating the impact of interdisciplinary research: A multilayer network approach

Published online by Cambridge University Press:  22 July 2016

ELISA OMODEI Open the ORCID record for ELISA OMODEI [Opens in a new window] ,
MANLIO DE DOMENICO  and
ALEX ARENAS
ELISA OMODEI
Affiliation:
Department of Mathematics and Computer Science, Rovira i Virgili University, Av. Països Catalans, 26, 43007 Tarragona, Spain (e-mail: [email protected], [email protected], [email protected])
MANLIO DE DOMENICO
Affiliation:
Department of Mathematics and Computer Science, Rovira i Virgili University, Av. Països Catalans, 26, 43007 Tarragona, Spain (e-mail: [email protected], [email protected], [email protected])
ALEX ARENAS
Affiliation:
Department of Mathematics and Computer Science, Rovira i Virgili University, Av. Països Catalans, 26, 43007 Tarragona, Spain (e-mail: [email protected], [email protected], [email protected])
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Abstract

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Nowadays, scientific challenges usually require approaches that cross traditional boundaries between academic disciplines, driving many researchers towards interdisciplinarity. Despite its obvious importance, there is a lack of studies on how to quantify the influence of interdisciplinarity on the research impact, posing uncertainty in a proper evaluation for hiring and funding purposes. Here, we propose a method based on the analysis of bipartite interconnected multilayer networks of citations and disciplines, to assess scholars, institutions, and countries interdisciplinary importance. Using data about physics publications and US patents, we show that our method allows to reward, using a quantitative approach, scholars and institutions that have carried out interdisciplinary work and have had an impact in different scientific areas. The proposed method could be used by funding agencies, universities and scientific policy decision makers for hiring and funding purposes, and to complement existing methods to rank universities and countries.

Keywords

citation networksinterconnected multilayer networksinterdisciplinarity
Type
Research Article
Information
Network Science , Volume 5 , Special Issue 2: Modeling, Analysis, and Mining of Multilayer Networks , June 2017 , pp. 235 - 246
Copyright
Copyright © Cambridge University Press 2016 

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