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Network analysis to measure academic performance in economics

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Abstract

Network analysis allows us to introduce different metrics that complement the traditional indicators to measure academic performance, generally based on individual production. In this paper, we show how the use of these techniques provides a more global point of view, introducing indicators that, beyond individual merits, measure the capacity of researchers to generate more intangible assets. We focus on collaboration among groups that can enrich the potential of the research ecosystem as a whole. We present not only numerical indicators, but also several visualisation schemes to see how this approach can help in the academic evaluation and decision-making process of research managers. We have used, as a case study, the research ecosystem formed by more than five thousand economists from Spanish institutions.

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References

  • Alvarez R, Cahué E, Clemente-gallardo J, Ferrer A, Iñíguez D, Mellado X, Rivero A, Ruiz G, Sanz F, Serrano E, Tarancón A, Vergara Y (2015) Analysis of academic productivity based on complex networks. Scientometrics 104:651–672

    Article  Google Scholar 

  • Andrikopoulos A, Economou L (2016) Coauthorship and subauthorship patters in financial economics. Int Rev Financ Anal 46:12–19

    Article  Google Scholar 

  • Araujo T, Fontainha E (2017) The specific shapes of gender imbalance in specific authorships: a network approach. J Informetr 11:88–102

    Article  Google Scholar 

  • Arroyo L, Gallardo-Gallardo E, Gallo P (2017) Understanding scientific communities: a social network approach to collaborations in talent management research. Scientometrics 113:1439–1462

    Article  Google Scholar 

  • Bergantiños G, Da Rocha JM, Polomé P (2002) La investigación española en Economía, 1995–1999. Investig Econ 26:373–392

    Google Scholar 

  • Bergé L, Scherngell T, Wanzenböck I (2017) Brinding centrality as an indicator to measure the “brinding role” of actors in networks: an application to the European Nanotechnology co-publication network. J Informetr 11:1031–1042

    Article  Google Scholar 

  • Boccaletti S, Latora V, Moreno Y, Chavez M, Hwang DU (2006) Complex networks: structure and dynamics. Phys Rep 424:175–308

    Article  Google Scholar 

  • Bordons M, Aparicio J, González-Albo B, Díaz-Faes A (2015) The relationship between the research performance of scientists and their position in co-authorship networks in three fields. J Informetr 9:135–144

    Article  Google Scholar 

  • Bornmann L, Stefaner M, de Moya F, Mutz R (2016) Excellence networks in science: a Web-based application based on Bayesian multilevel logistic regression (BMLR) for the identification of institutions collaborating successfully. J Informetr 10:312–327

    Article  Google Scholar 

  • Card D, DellaVigna S (2013) Nine facts about top journals in economics. J Econ Lit 51(19):144–161

    Article  Google Scholar 

  • Carrasco R, Ruiz-Castillo J (2014) The evolution of the scientific productivity of highly productive economists. Econ Inq 52:1–16

    Article  Google Scholar 

  • Clauset A, Shalizi CR, Newman MEJ (2009) Power law distributions in empirical data. SIAM Rev 51:661–703

    Article  Google Scholar 

  • Clerides S, Pashardes P, Polycarpou A (2011) Peer review vs metric-based assessment: testing for bias in the RAE ratings of UK economics departments. Economica 78(311):565–583

    Article  Google Scholar 

  • Cobo MJ, López-Herrera AG, Herrera-Viedma E, Herrera F (2011) Science mapping software tools: review, analysis, and cooperative study among tools. J Am Soc Inf Sci Technol 62(7):1382–1402

    Article  Google Scholar 

  • Colavizza G (2017) The structural role of the core literature in history. Scientometrics 113:1787–1809

    Article  Google Scholar 

  • Costa L, Siqueira M, Alves L, Motta E (2017) Growth patterns of the network of international collaboration in science. Scientometrics. https://doi.org/10.10007/s11192-017-2573x

    Article  Google Scholar 

  • de Price DJS (1965) Networks of scientific papers. Science 149(3683):510–515

    Article  Google Scholar 

  • Ding Y, Yan E, Frazho A, Caverlee J (2009) PageRank for ranking authors in co-citation networks. J Am Soc Inf Sci Technol 60(11):2229–2243

    Article  Google Scholar 

  • Ductor L (2016) Does co-authorship lead to higher academic productivity? Oxf Bull Econ Stat 77(3):385–407

    Article  Google Scholar 

  • Dusansky R, Vernon CJ (1998) Rankings of U.S. economics departments. J Econ Perspect 12:157–170

    Article  Google Scholar 

  • Fruchterman TMJ, Reingold EM (1991) Graph drawing by force-directed. Softw Pract Exp 21(11):1129

    Article  Google Scholar 

  • Goyal S, Van Der Leij MJ, Moraga-González JL (2006) Economics: an emerging small world. J Polit Econ 114(2):403–412

    Article  Google Scholar 

  • Hamermesh DS (2015) Citations in economics: measurement, uses and impacts. IZA DP no. 9593

  • Inzelt A, Schubert A, Schubert M (2009) Incremental citation impact due to international co-authorship in Hugarian higher education institutions. Scientometrics 78:37–43

    Article  Google Scholar 

  • Kalaitzideakis P, Mamuneas TP, Stengos T (1999) European economics: an analysis based in publications in the core journals. Eur Econ Rev 43:1150–1168

    Article  Google Scholar 

  • Kalaitzideakis P, Mamuneas TP, Stengos T (2003) Rankings of academic journals and institutions in economics. J Eur Econ Assoc 1(6):1343–1366

    Google Scholar 

  • Kalaitzideakis P, Mamuneas TP, Stengos T (2011) An updated ranking of academic journals in economics. Can J Econ 44(4):1525–1538

    Article  Google Scholar 

  • Katranidis S, Panagiotidis T, Zontanos C (2014) An evaluation of the Greek universities’ economics departments. Bull Econ Res 66(2):173–182

    Article  Google Scholar 

  • Katranidis S, Panagiotidis T, Zontanos C (2017) Economists, research performance and national inbreeding: north versus south. Econ Notes 46(1):145–163

    Article  Google Scholar 

  • Kumar S (2015) Co-authorship networks: a review of the literature. Aslib J Inf Manag 67(1):55–73

    Article  Google Scholar 

  • Kyvik S, Reymert I (2017) Research collaboration in groups and networks: differences across academic fields. Scientometrics 113:951–967

    Article  Google Scholar 

  • Letina S (2016) Network and actor attribute effects on the performance of researchers in two fields of social science in a small peripheral community. J Informetr 10:571–595

    Article  Google Scholar 

  • Levenshtein I (1996) Binary codes capable of correcting deletions, insertions and reversals. Cybern Control Theory 10:7076710

    Google Scholar 

  • Liebowitz SJ, Palmer JP (1984) Assessing the relative impacts of economic journals. J Econ Lit 22:77–88

    Google Scholar 

  • Macri M, Sinha D (2006) Rankings methodology for international comparisons of institutions and individuals: an application to economics in Australia and New Zealand. J Econ Surv 20:111–156

    Article  Google Scholar 

  • Moosa IA (2016) Citations, journal ranking and multiple authorships: evidence based on the top 300 papers in economics. Appl Econ Lett. https://doi.org/10.1080/13504851.2016.1176104

    Article  Google Scholar 

  • Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74(3):036104

    Article  Google Scholar 

  • Newman MEJ (2010) Networks: an introduction. Oxford University Press, Oxford

    Book  Google Scholar 

  • Nowell C, Grijalva T (2011) Trends in co-authorship in economics since 1985. Appl Econ 43:4359–4375

    Article  Google Scholar 

  • Oswald AJ (2007) An examination of the reliability of prestigious scholarly journals: evidence and implications for decision-makers. Economica 74:21–31

    Article  Google Scholar 

  • Padial AA, Nabout JC, Wiqueira T, Bini LM, Diniz-Filho JAF (2010) Weak evidence for determinants of citation frequency in ecological articles. Scientometrics 85:1–12

    Article  Google Scholar 

  • Parreira M, Machado K, Logares R, Diniz-Filho J, Nabout JC (2017) The roles of geographic distance and socioeconomic factors on international collaboration among ecologists. Scientometrics 113:1539–1550

    Article  Google Scholar 

  • Perc M (2010) Growth and structure of Slovenia’s scientific collaboration network. J Informetr 4:475–482

    Article  Google Scholar 

  • Perianes-Rodriguez A, Ludo Waltman L, van Eck NJ (2016) Constructing bibliometric networks: a comparison between full and fractional counting. J Informetr 10:1178–1195

    Article  Google Scholar 

  • Polyakov M, Polyakov S, Iftekhar S (2017) Does academic collaboration equally benefit impact of research across topics? The case of agricultural, resource, environmental and ecological economics. Scientometrics 113:1385–1405

    Article  Google Scholar 

  • Pons P, Latapy M (2006) Computing communities in large networks using random walks. J Graph Algorithms Appl 10(2):191–218

    Article  Google Scholar 

  • Rainho O, Cointet J, Cambrosio A (2017) Oncology research in late twentieth century and turn of the century Portugal: a scientometric approach to its institutional and semantic dimensions. Scientometrics 113(2):867–888

    Article  Google Scholar 

  • Rath K, Wohlrabe K (2015) Recent trends in co-authorship in economics: evidence from RePEc. Appl Econ Lett. https://doi.org/10.1080/13504851.2015.1119783

    Article  Google Scholar 

  • Robert C, Arreto C, Azerad J, Gaudy J (2004) Bibliometric overview of the utilization of artificial neural networks in medicine and biology. Scientometrics 59:117–130

    Article  Google Scholar 

  • Ruiz-Castillo J, Carrasco R, Albarrán P (2014) The elite in economics. UC3M Working papers. Economics we1414, Universidad Carlos III de Madrid. Departamento de Economía.

  • Schubert A (2014) Sentences to remember from the first 100 volumes of the journal scientometrics. Scientometrics 100:1–13

    Article  Google Scholar 

  • Sutter M, Kocher M (2004) Patterns of co-authorship among economics departments in the USA. Appl Econ 36(4):327–333

    Article  Google Scholar 

  • Tang M, Cheng Y, Chen K (2017) A longitudinal study of intellectual cohesion in digital humanities using bibliometric analysis. Scientometrics 113:985–1008

    Article  Google Scholar 

  • Waltman L, van Eck NJ, Wouters P (2009) Counting publications and citations: is more always better? J Informetr 7:635–641

    Article  Google Scholar 

Download references

Acknowledgements

This paper was partially written while Jose Alberto Molina was Visiting Fellow at the Department of Economics of Boston College (US), to which he would like to express his thanks for the hospitality and facilities provided. Kampal Data Solutions S.L. thanks Web of Science for permission to publish the analysis of these data on its web page (research.kampal.com). This paper has benefited from funding from the Spanish Ministry of Economics (Projects ECO2012-34828 and FIS2015-65078-C2-2-P), and it has been dedicated to A. Calvo-Armengol, an expert in social networks, who died prematurely in 2007.

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Authors and Affiliations

  1. Department of Economics, Faculty of Economics, University of Zaragoza, Gran Vía 2, 50005, Zaragoza, Spain

    José Alberto Molina

  2. Department of Theoretical Physics, University of Zaragoza, Zaragoza, Spain

    Alfonso Tarancón

  3. ARAID Foundation, Government of Aragón, Zaragoza, Spain

    David Iñiguez

  4. Institute for Biocomputation and Physics of Complex Systems (BIFI), Zaragoza, Spain

    José Alberto Molina, Alfredo Ferrer, David Iñiguez, Alejandro Rivero, Gonzalo Ruiz & Alfonso Tarancón

  5. Kampal Data Solutions S.L., 50001, Zaragoza, Spain

    Alfredo Ferrer, David Iñiguez, Alejandro Rivero, Gonzalo Ruiz & Alfonso Tarancón

  6. Institute for the Study of Labor-IZA, Bonn, Germany

    José Alberto Molina

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  1. José Alberto Molina
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  2. Alfredo Ferrer
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  4. Alejandro Rivero
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Correspondence to José Alberto Molina.

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Molina, J.A., Ferrer, A., Iñiguez, D. et al. Network analysis to measure academic performance in economics. Empir Econ 58, 995–1018 (2020). https://doi.org/10.1007/s00181-018-1546-0

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