Hostname: page-component-7b7567c8c-2n9c9 Total loading time: 0 Render date: 2026-11-14T10:15:36.544Z Has data issue: false hasContentIssue false
  • English
  • Français

Evaluating the impact of interdisciplinary research: A multilayer network approach

Published online by Cambridge University Press:  22 July 2016

ELISA OMODEIOpen 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: elisa.omodei@urv.cat, manlio.dedomenico@urv.cat, alexandre.arenas@urv.cat)
MANLIO DE DOMENICO
Affiliation:
Department of Mathematics and Computer Science, Rovira i Virgili University, Av. Països Catalans, 26, 43007 Tarragona, Spain (e-mail: elisa.omodei@urv.cat, manlio.dedomenico@urv.cat, alexandre.arenas@urv.cat)
ALEX ARENAS
Affiliation:
Department of Mathematics and Computer Science, Rovira i Virgili University, Av. Països Catalans, 26, 43007 Tarragona, Spain (e-mail: elisa.omodei@urv.cat, manlio.dedomenico@urv.cat, alexandre.arenas@urv.cat)
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the 'Save PDF' action button.

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

Information

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 

References

Bergstrom, C. (2007). Measuring the value and prestige of scholarly journals. College & Research Libraries News, 68 (5), 314–316.CrossRefGoogle Scholar
Bornmann, L., Mutz, R., & Daniel, H.-D. (2008). Are there better indices for evaluation purposes than the h index? a comparison of nine different variants of the h index using data from biomedicine. Journal of the American Society for Information Science and Technology, 59 (5), 830–837.CrossRefGoogle Scholar
Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual web search engine. Computer Networks and isdn Systems, 30 (1), 107–117.CrossRefGoogle Scholar
De Domenico, M., Solé-Ribalta, A., Cozzo, E., Kivelä, M., Moreno, Y., Porter, M. A.,. . .Arenas, A. (2013). Mathematical formulation of multilayer networks. Physical Review x, 3 (4), 041022.CrossRefGoogle Scholar
De Domenico, M., Solé-Ribalta, A., Omodei, E., Gómez, S., & Arenas, A. (2015). Ranking in interconnected multilayer networks reveals versatile nodes. Nature Communications, 6, 6868.Google Scholar
de Solla Price, D. J. (1965). Networks of scientific papers. Science, 149 (3683), 510–515.Google Scholar
Deville, P., Wang, D., Sinatra, R., Song, C., Blondel, V. D., & Barabási, A.-L. (2014). Career on the move: Geography, stratification, and scientific impact. Scientific Reports, 4, 4770.Google Scholar
Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69 (1), 131–152.CrossRefGoogle Scholar
Eom, Y. H., Fortunato, S., & Perc, M. (2011). Characterizing and modeling citation dynamics. Plos one, 6 (9), e24926.Google Scholar
Garfield, E., & Merton, R. K. (1979). Citation indexing: Its theory and application in science, technology, and humanities Vol. 8. New York: Wiley.Google Scholar
Gauffriau, M., Larsen, P., Maye, I., Roulin-Perriard, A., & von Ins, M. (2008). Comparisons of results of publication counting using different methods. Scientometrics, 77 (1), 147–176.Google Scholar
Glänzel, W., Debackere, K., Thijs, B., & Schubert, A. (2006). A concise review on the role of author self-citations in information science, bibliometrics and science policy. Scientometrics, 67 (2), 263–277.Google Scholar
Guimera, R., Uzzi, B., Spiro, J., & Amaral, L. A. N. (2005). Team assembly mechanisms determine collaboration network structure and team performance. Science, 308 (5722), 697–702.Google Scholar
Hall, B. H., Jaffe, A. B., & Trajtenberg, M. (2001). The nber patent citation data file: Lessons, insights and methodological tools. Tech. rept. National Bureau of Economic Research.Google Scholar
Hirsch, J. E. (2005). An index to quantify an individual's scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102 (46), 16569–16572.CrossRefGoogle ScholarPubMed
Jensen, P., & Lutkouskaya, K. (2014). The many dimensions of laboratories interdisciplinarity. Scientometrics, 98 (1), 619–631.Google Scholar
Kaur, J., Radicchi, F., & Menczer, F. (2013). Universality of scholarly impact metrics. Journal of Informetrics, 7 (4), 924–932.Google Scholar
Ke, Q., Ferrara, E., Radicchi, F., & Flammini, A.. (2015). Defining and identifying sleeping beauties in science. Proceedings of the National Academy of Sciences, 112 (24), 7426–7431.Google Scholar
King, D. A. (2004). The scientific impact of nations. Nature, 430 (6997), 311–316.Google Scholar
Kivelä, M., Arenas, A., Barthelemy, M., Gleeson, J. P., Moreno, Y., & Porter, M. A. (2014). Multilayer networks. Journal of Complex Networks, 2 (3), 203–271.Google Scholar
Larivière, V., Haustein, S., & Börner, K. (2015). Long-distance interdisciplinarity leads to higher scientific impact. Plos one, 10 (3), e0122565.Google Scholar
Leydesdorff, L. (2007). Betweenness centrality as an indicator of the interdisciplinarity of scientific journals. Journal of the American Society for Information Science and Technology, 58 (9), 1303–1319.Google Scholar
Li, Y., Radicchi, F., Castellano, C. & Ruiz-Castillo, J. (2013). Quantitative evaluation of alternative field normalization procedures. Journal of Informetrics, 7 (3), 746–755.Google Scholar
Nature. (2015). Mind meld. Nature, 525, 289–290.Google Scholar
Newman, M. E. J. (2009). The first-mover advantage in scientific publication. Epl (Europhysics Letters), 86 (6), 68001.Google Scholar
Pan, L., & Katrenko, S. (2015). A review of the uks interdisciplinary research using a citation-based approach. Amsterdam, Netherlands: Elsevier.Google Scholar
Penner, O., Pan, R. K., Petersen, A. M., Kaski, K., & Fortunato, S. (2013). On the predictability of future impact in science. Scientific Reports, 3, 3052.Google Scholar
Porter, A. L., Cohen, A. S., Roessner, J. D., & Perreault, M. (2007). Measuring researcher interdisciplinarity. Scientometrics, 72 (1), 117–147.CrossRefGoogle Scholar
Radicchi, F., Fortunato, S., & Castellano, C. (2008). Universality of citation distributions: Toward an objective measure of scientific impact. Proceedings of the National Academy of Sciences, 105 (45), 17268–17272.Google Scholar
Radicchi, F., Fortunato, S., Markines, B., & Vespignani, A. (2009). Diffusion of scientific credits and the ranking of scientists. Physical Review E, 80 (5), 056103.Google Scholar
Redner, S. (1998). How popular is your paper? an empirical study of the citation distribution. The European Physical Journal B-Condensed Matter and Complex Systems, 4 (2), 131–134.Google Scholar
Rhoten, D., & Parker, A. (2004). Risks and rewards of an interdisciplinary research path. Science(Washington), 306 (5704), 2046.Google Scholar
Sinatra, R., Deville, P., Szell, M., Wang, D., & Barabási, A.-L. (2015). A century of physics. Nature Physics, 11 (10), 791–796.CrossRefGoogle Scholar
Uzzi, B., Mukherjee, S., Stringer, M., & Jones, B. (2013). Atypical combinations and scientific impact. Science, 342 (6157), 468–472.Google Scholar
Wagner, C. S., Roessner, J. D., Bobb, K., Klein, J. T., Boyack, K. W., Keyton, J.,. . .Börner, K. (2011). Approaches to understanding and measuring interdisciplinary scientific research (idr): A review of the literature. Journal of Informetrics, 5 (1), 14–26.Google Scholar
Walker, D., Xie, H., Yan, K.-K., & Maslov, S. (2007). Ranking scientific publications using a model of network traffic. Journal of Statistical Mechanics: Theory and Experiment, 2007 (06), P06010.Google Scholar
Wang, D., Song, C., & Barabási, A.-L. (2013). Quantifying long-term scientific impact. Science, 342 (6154), 127–132.CrossRefGoogle ScholarPubMed
Wang, J. (2013). Citation time window choice for research impact evaluation. Scientometrics, 94 (3), 851–872.Google Scholar
Zhang, Q., Perra, N., Gonçalves, B., Ciulla, F., & Vespignani, A. (2013). Characterizing scientific production and consumption in physics. Scientific Reports, 3, 1640.Google Scholar
Supplementary material: PDF

Omodei supplementary material

Omodei supplementary material 1

Download Omodei supplementary material(PDF)
PDF 1.6 MB