Skip to main content
SpringerLink
Log in

Analysis of academic productivity based on Complex Networks

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

We present a new tool, Kampal (http://kampal.unizar.es), developed to help to analyze the academic productivity of a research institution from the point of view of Complex Networks. We will focus on two main aspects: paper production and funding by research grants. Thus, we define a network of researchers and define suitable ways of describing their interaction, either by co-publication, project-collaboration, or a combination of both. From the corresponding complex networks, we extract maps which encode in graphical terms the relevant information and numerical parameters which encode the topological properties of the network. Thousands of these maps have been created and allow us to study the similarities and differences of the co-publications and the project-collaboration networks.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  • Abbas, A. M. (2011). Weighted indices for evaluating the quality of research with multiple authorship. Scientometrics, 88(1), 107–131.

    Article  Google Scholar 

  • Abbasi, A., Altmann, J., & Hwang, J. (2010). Evaluating scholars based on their academic collaboration activities: Two indices, the RC-index and the CC-index, for quantifying collaboration activities of researchers and scientific communities. Scientometrics, 83(1), 1–13.

    Article  Google Scholar 

  • Abramo, G., D’Angelo, C. A., & Viel, F. (2013). The suitability of h and g indexes for measuring the research performance of institutions. Scientometrics, 97(3), 555–570.

    Article  Google Scholar 

  • Alonso, S., Cabrerizo, F., Herrera-Viedma, E., & Herrera, F. (2009). h-Index: A review focused in its variants, computation and standardization for different scientific fields. Journal of Informetrics, 3(4), 273–289.

    Article  Google Scholar 

  • Barrat, A., Barthélemy, M., Pastor-Satorras, R., & Vespignani, A. (2004). The architecture of complex weighted networks. PNAS, 101(11), 3747–3752.

    Article  Google Scholar 

  • Batista, P., Campiteli, M., Kinouchi, O., & Martinez, A. S. (2006). Is it possible to compare researchers with different scientific interests? Scientometrics, 68(1), 179–189.

    Article  Google Scholar 

  • Bordons, M., & Barrigón, S. (1992). Bibliometric analysis of publications of Spanish pharmacologists in the SCI (1984–89). Part II. Scientometrics, 25(3), 425–446.

    Article  Google Scholar 

  • Borgatti, S. P. (2005). Centrality and network flow. Social Networks, 27(1), 55–71.

    Article  Google Scholar 

  • Borgatti, S. P., & Everett, M. G. (2006). A Graph-theoretic perspective on centrality. Social Networks, 28(4), 466–484.

    Article  Google Scholar 

  • Brin, S., & Page, L. (1998). The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems, 30(1–7), 107–117.

    Article  Google Scholar 

  • Brin, S., & Page, L. (2012). Reprint of: The anatomy of a large-scale hypertextual web search engine. Computer Networks, 56(18), 3825–3833.

    Article  Google Scholar 

  • Cobo, M. J., López-Herrera, A. G., Herrrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools : Review, analysis, and cooperative study among tools. J Am Soc Inf Science Tech, 62(7), 1382–1402.

    Article  Google Scholar 

  • Costas, R., & Bordons, M. (2007). The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level. Journal of Informetrics, 1(3), 193–203.

    Article  Google Scholar 

  • Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. InterJournal, Complex Systems, 1695. http://igraph.org.

  • Di Caro, L., Cataldi, M., & Schifanella, C. (2012). The d-index: Discovering dependences among scientific collaborators from their bibliographic data records. Scientometrics, 93(3), 583–607.

    Article  Google Scholar 

  • Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152.

    Article  MathSciNet  Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks conceptual clarification. Social Networks, 1(3), 215–239.

    Article  Google Scholar 

  • Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129–1164.

    Google Scholar 

  • Grauwin, S., & Jensen, P. (2011). Mapping scientific institutions. Scientometrics, 89(3), 943–954.

    Article  Google Scholar 

  • Hirsch, J. (2005). An index to quantify an individual’s scientific research output. PNAS, 102(46), 16569–16572.

    Article  Google Scholar 

  • Iglesias, J. E., & Pecharromán, C. (2007). Scaling the h-index for different scientific ISI fields. Scientometrics, 73(3), 303–320.

    Article  Google Scholar 

  • Ladyman, J., Lambert, J., & Wiesner, K. (2013). What is a complex system? European Journal for Philosophy of Science, 3(1), 33–67.

    Article  MATH  Google Scholar 

  • Mryglod, O., Kenna, R., Holovatch, Y., & Berche, B. (2013). Comparison of a citation-based indicator and peer review for absolute and specific measures of research-group excellence. Scientometrics, 97(3), 767–777.

    Article  Google Scholar 

  • Newman, M. E. J. (2001a). Scientific collaboration networks. I: Network construction and fundamental results. Physical Review E, 64(1), 016,131.

    Article  Google Scholar 

  • Newman, M. E. J. (2001b). The structure of scientific collaboration networks. PNAS, 98(2), 9–404.

    Article  Google Scholar 

  • Newman, M. E. J. (2001c). Scientific collaboration networks, II: Shortest paths, weighted networks, and centrality. Physical Review E, 64(1), 016,132.

    Article  Google Scholar 

  • Newman, M. E. J. (2006). Finding community structure in networks using the eigenvectors of matrices. Physical Review E, 74(3), 036,104.

    Article  Google Scholar 

  • Opsahl, T., Agneessens, F., & Skvoretz, J. (2010). Node centrality in weighted networks: Generalizing degree and shortest paths. Social Networks, 32(3), 245–251.

    Article  Google Scholar 

  • Pons, P., & Latapy, M. (2006). Computing communities in large networks using random walks. Journal of Graph Algorithms and Applications, 10(2), 191–218.

    Article  MathSciNet  MATH  Google Scholar 

  • Price, D. (1965). Networks of scientific papers. Science, 149(3683), 510–515.

    Article  Google Scholar 

  • Rafols, I., Porter, A. L., & Leydesdorff, L. (2010). Science overlay maps: A new tool for research policy and library management. Journal of Ameican Society for Information Science and Technology, 61(9), 1871–1887.

    Article  Google Scholar 

  • Ruocco, G., & Daraio, C. (2013). An empirical approach to compare the performance of heterogeneous academic fields. Scientometrics, 97(3), 601–625.

    Article  Google Scholar 

  • Salton, G., & McGill, M. J. (1987). Introduction to modern information retrieval. New York: McGraw-Hill.

    Google Scholar 

  • Strang, G. (2005). Linear algebra and its applications (4th ed.). Boston, MA: Cengage Learning.

    Google Scholar 

  • Torrisi, B. (2014). A multidimensional approach to academic productivity. Scientometrics, 99, 755–783.

    Article  Google Scholar 

  • Van Eck, N. J., & Waltman, L. (2009). How to normalize cooccurende data? An analysis of some well-known similarity measures. Journal of the American Society for Information Science and Technology, 60(8), 1635–1651.

    Article  Google Scholar 

  • Wallace, D. L. (1983). Comment to “A method for comparing two hierarchical clusterings”. Journal of the American Statistical Association, 78(383), 569–576.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Edificio I+D, Instituto de Biocomputación y Física de los Sistemas Complejos, Universidad de Zaragoza, Campus Río Ebro, C/ Mariano Esquillor s/n, 50018, Zaragoza, Spain

    R. Álvarez, E. Cahué, J. Clemente-Gallardo, A. Ferrer, D. Íñiguez, X. Mellado, A. Rivero, G. Ruiz, F. Sanz, A. Tarancón & Y. Vergara

  2. Departmento de Física Teórica, Universidad de Zaragoza, Campus San Francisco, 50009, Zaragoza, Spain

    J. Clemente-Gallardo & A. Tarancón

  3. Universidad de Zaragoza, Campus San Francisco, 50009, Zaragoza, Spain

    E. Serrano

Authors
  1. R. Álvarez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. E. Cahué
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. J. Clemente-Gallardo
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. A. Ferrer
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. D. Íñiguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. X. Mellado
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. A. Rivero
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. G. Ruiz
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. F. Sanz
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. E. Serrano
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. A. Tarancón
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Y. Vergara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to J. Clemente-Gallardo.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Álvarez, R., Cahué, E., Clemente-Gallardo, J. et al. Analysis of academic productivity based on Complex Networks. Scientometrics 104, 651–672 (2015). https://doi.org/10.1007/s11192-015-1627-1

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-015-1627-1

Keywords

Search

Navigation