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Evaluating the impact of interdisciplinary research: A multilayer network approach

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  • OMODEI, ELISA
  • DE DOMENICO, MANLIO
  • ARENAS, ALEX

Abstract

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.

Suggested Citation

  • Omodei, Elisa & De Domenico, Manlio & Arenas, Alex, 2017. "Evaluating the impact of interdisciplinary research: A multilayer network approach," Network Science, Cambridge University Press, vol. 5(2), pages 235-246, June.
  • Handle: RePEc:cup:netsci:v:5:y:2017:i:02:p:235-246_00
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    Cited by:

    1. Juste Raimbault, 2019. "Exploration of an interdisciplinary scientific landscape," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 617-641, May.
    2. Shahadat Uddin & Tasadduq Imam & Mohammad Mozumdar, 2021. "Research interdisciplinarity: STEM versus non-STEM," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 603-618, January.
    3. Juste Raimbault & Pierre-Olivier Chasset & Clémentine Cottineau & Hadrien Commenges & Denise Pumain & Christine Kosmopoulos & Arnaud Banos, 2021. "Empowering open science with reflexive and spatialised indicators," Environment and Planning B, , vol. 48(2), pages 298-313, February.
    4. Zaifang Zhang & Darao Xu & Egon Ostrosi & Hui Cheng, 2020. "Optimization of the Product–Service System Configuration Based on a Multilayer Network," Sustainability, MDPI, vol. 12(2), pages 1-25, January.
    5. Higham, Kyle & Contisciani, Martina & De Bacco, Caterina, 2022. "Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    6. Aleja, David & Criado, Regino & García del Amo, Alejandro J. & Pérez, Ángel & Romance, Miguel, 2019. "Non-backtracking PageRank: From the classic model to hashimoto matrices," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 283-291.
    7. Samarth Kumar & Christoph Zöphel & Anna Martius & Rengin Cabadag & Frederik Plewnia & Nick Pruditsch & Bastian A. Sakowski & Dominik Möst, 2019. "Stronger together—A framework for measuring interdisciplinary understanding," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(6), November.

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