Skip to main content
SpringerLink
Log in

A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Co-authorship networks have been used to study collaboration patterns in various fields, evaluate researchers and recommend policies. In their simplest form they are constructed by considering authors to be network nodes connected to each other if they published a paper together. We propose to further explore the same data by constructing a different network, in which nodes are articles linked to one another if they have a common author. For papers published in the fields of computer science and mathematics with affiliations to Romanian institutions, we show that this type of network reveals patterns of collaborative behavior and offers new insights about practices in the field. We find that the proposed networks are smaller and denser than the co-authorship networks, have a better defined community structure, and directly represent the results of collaborative endeavors by focusing on the actual outcome, i.e., published papers.

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

Similar content being viewed by others

Notes

  1. Essential Science Indicators, Thomson Reuters.

  2. www.scopus.com, accessed October, 2015.

  3. Generated by using the CartoDB software, www.cartodb.com.

  4. http://gephi.github.io/.

  5. By using the source code available at http://sites.google.com/site/andrealancichinetti/software.

References

  • Abbasi, A., Chung, K. S. K., & Hossain, L. (2012a). Egocentric analysis of co-authorship network structure, position and performance. Information Processing and Management, 48(4), 671–679.

    Article  Google Scholar 

  • Abbasi, A., Hossain, L., & Leydesdorff, L. (2012b). Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks. Journal of Informetrics, 6(3), 403–412.

    Article  Google Scholar 

  • Ahn, S. A., & Jung, Y. (2015). High performance computing research activity: Co-authorship network analysis. ICIC Express Letters, Part B: Applications, 6(5), 1437–1441.

    Google Scholar 

  • Amblard, F., Casteigts, A., Flocchini, P., Quattrociocchi, W., & Santoro, N. (2011). On the temporal analysis of scientific network evolution. In 2011 International Conference on Computational Aspects of Social Networks (CASoN), IEEE, pp. 169–174.

  • Barabási, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    Article  MathSciNet  MATH  Google Scholar 

  • Barabási, A. L., Jeong, H., Néda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A: Statistical Mechanics and its Applications, 311(3), 590–614.

    Article  MathSciNet  MATH  Google Scholar 

  • Blondel, V. D., Guillaume, J. L., Lambiotte, R., & Lefebvre, E. (2008). Fast unfolding of communities in large networks. Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10,008.

    Article  Google Scholar 

  • Bordons, M., Aparicio, J., González-Albo, B., & Díaz-Faes, A. A. (2015). The relationship between the research performance of scientists and their position in co-authorship networks in three fields. Journal of Informetrics, 9(1), 135–144.

    Article  Google Scholar 

  • Cardillo, A., Scellato, S., & Latora, V. (2006). A topological analysis of scientific coauthorship networks. Physica A: Statistical Mechanics and its Applications, 372(2), 333–339.

    Article  Google Scholar 

  • Cheong, F., & Corbitt, B. (2009). A social network analysis of the co-authorship network of the australasian conference of information systems from 1990 to 2006. In 17th European Conference on Information Systems, ECIS 2009.

  • Chubin, D. E., & Studer, K. E. (1979). Knowledge and structures of scientific growth measurement of a cancer problem domain. Scientometrics, 1(2), 171–193.

    Article  Google Scholar 

  • Cugmas, M., Ferligoj, A., & Kronegger, L. (2016). The stability of co-authorship structures. Scientometrics, 106(1), 163–186.

    Article  Google Scholar 

  • Delgado-Garcia, J.F., Laender, A.H., & Meira, W. (2014). Analyzing the Coauthorship Networks of Latin American Computer Science Research Groups. In 9th Latin American Web Congress, IEEE, pp 77–81.

  • Ding, Y. (2011). Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks. Journal of informetrics, 5(1), 187–203.

    Article  Google Scholar 

  • Fortunato, S. (2010). Community detection in graphs. Physics Reports, 486, 75–174.

    Article  MathSciNet  Google Scholar 

  • Ghafouri, H. B., Mohammadhassanzadeh, H., Shokraneh, F., Vakilian, M., & Farahmand, S. (2013). Social network analysis of Iranian researchers on emergency medicine: A sociogram analysis. Emergency Medicine Journal, 31(8), 619–624.

    Article  Google Scholar 

  • Giuliani, F., De Petris, M. P., & Nico, G. (2010). Assessing scientific collaboration through coauthorship and content sharing. Scientometrics, 85(1), 13–28.

    Article  Google Scholar 

  • Glänzel, W. (2001). National characteristics in international scientific co-authorship relations. Scientometrics, 51(1), 69–115.

    Article  Google Scholar 

  • Glänzel, W. (2002). Coauthorship patterns and trends in the sciences (1980–1998): A bibliometric study with implications for database indexing and search strategies. Library Trends, 50(3), 461–473.

    Google Scholar 

  • Glänzel, W., & Schubert, A. (2005). Handbook of quantitative science and technology research: The use of publication and patent statistics in studies of S&T systems (pp. 257–276). Dordrecht: Springer.

    Book  Google Scholar 

  • Han, Y., Zhou, B., Pei, J., & Jia, Y. (2009). Understanding importance of collaborations in co-authorship networks: A supportiveness analysis approach. In Society for Industrial and Applied Mathematics - 9th SIAM International Conference on Data Mining 2009, Proceedings in Applied Mathematics, vol 3, pp. 1105–1116.

  • Hâncean, M. G., Perc, M., & Vlăsceanu, L. (2014). Fragmented romanian sociology: Growth and structure of the collaboration network. PloS One, 9(11), e113,271.

    Article  Google Scholar 

  • He, B., Ding, Y., Tang, J., Reguramalingam, V., & Bollen, J. (2013). Mining diversity subgraph in multidisciplinary scientific collaboration networks: A meso perspective. Journal of Informetrics, 7(1), 117–128.

    Article  Google Scholar 

  • Huang, J., Zhuang, Z., Li, J., & Giles, C.L. (2008). Collaboration over time: characterizing and modeling network evolution. In Proceedings of the 2008 International Conference on Web Search and Data Mining, ACM, pp. 107–116.

  • Kretschmer, H., Ozel, B., & Kretschmer, T. (2015a). Who is collaborating with whom? Part I. Mathematical model and methods for empirical testing. Journal of Informetrics, 9(2), 359–372.

    Article  Google Scholar 

  • Kretschmer, H., Ozel, B., & Kretschmer, T. (2015b). Who is collaborating with whom? Part II. Application of the methods to male and to female networks. Journal of Informetrics, 9(2), 373–384.

    Article  Google Scholar 

  • Kumar, S. (2015). Co-authorship networks: A review of the literature. Aslib Journal of Information Management, 67(1), 55–73.

    Article  Google Scholar 

  • Kumar, S. (2016). Effect of gender on collaborative associations of researchers in Malaysia. The Electronic Library, 34(1), 74–82.

    Article  Google Scholar 

  • Kurosawa, T., & Takama, Y. (2012). Co-Authorship networks visualization system for supporting survey of researchers future activities. Journal of Emerging Technologies in Web Intelligence, 4(1), 3–14.

    Article  Google Scholar 

  • Lancichinetti, A., Radicchi, F., Ramasco, J. J., & Fortunato, S. (2011). Finding statistically significant communities in networks. PloS One, 6(4), e18,961.

    Article  Google Scholar 

  • Li, L., & Xuezhu, G. (2012). Innovation performance of university co-authorship network. In Information Management, Innovation Management and Industrial Engineering (ICIII), 2012 International Conference on, IEEE, vol 1, pp 410–413.

  • Liu, J., Li, Y., Ruan, Z., Fu, G., Chen, X., Sadiq, R., et al. (2015). A new method to construct co-author networks. Physica A: Statistical Mechanics and its Applications, 419, 29–39.

    Article  Google Scholar 

  • Liu, Y.X., Lu, B., & Zhang, Q. (2013). Empirical analysis of the coauthorship network based on DBLP. In International Conference on Machine Learning and Cybernetics, IEEE, vol 3, pp 1070–1076.

  • Logan, E. L., & Shaw, W. M. (1991). A bibliometric analysis of collaboration in a medical specialty. Scientometrics, 20(3), 417–426.

    Article  Google Scholar 

  • Lozano, S., Rodríguez, X. P., & Arenas, A. (2013). Atapuerca: evolution of scientific collaboration in an emergent large-scale research infrastructure. Scientometrics, 98(2), 1505–1520.

    Article  Google Scholar 

  • Lužar, B., Levnajić, Z., Povh, J., & Perc, M. (2014). Community structure and the evolution of interdisciplinarity in slovenia’s scientific collaboration network. PLoS One, 9(4), e94,429.

    Article  Google Scholar 

  • Matusiak, A., & Morzy, M. (2012). Social Network Analysis in Scientometrics. In 2012 Eighth International Conference on Signal Image Technology and Internet Based Systems, IEEE, pp. 692–699.

  • Mena-Chalco, J.P., & Cesar Junior, R.M. (2011). Towards Automatic Discovery of co-authorship Networks in the Brazilian Academic Areas. In 2011 IEEE Seventh International Conference on e-Science Workshops, IEEE, pp. 53–60.

  • Meng, W., & Pang, J. (2010). Analysis of network characteristic and community structure of co-authorship network for information science in China. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 35(Special Issue 2), 102–106.

    Google Scholar 

  • Milojević, S. (2010). Modes of collaboration in modern science: Beyond power laws and preferential attachment. Journal of the American Society for Information Science and Technology, 61(7), 1410–1423.

    Article  Google Scholar 

  • Nikzad, M., Jamali, H. R., & Hariri, N. (2011). Patterns of Iranian co-authorship networks in social sciences: A comparative study. Library and Information Science Research, 33(4), 313–319.

    Article  Google Scholar 

  • Olmeda-Gómez, C., Perianes-Rodríguez, A., Antonia Ovalle-Perandones, M., Guerrero-Bote, V. P., & de Moya, Anegón F. (2009). Visualization of scientific coauthorship in Spanish universities. Aslib Proceedings, 61(1), 83–100.

    Article  Google Scholar 

  • Ortega, J. L. (2014). Influence of co-authorship networks in the research impact: Ego network analyses from Microsoft Academic Search. Journal of Informetrics, 8(3), 728–737.

    Article  Google Scholar 

  • Ovalle-Perandones, M.A., Perianes-Rodriguez, A., & Olmeda-Gomez, C. (2009). Hubs and Authorities in a Spanish Co-authorship Network. In 2009 13th International Conference Information Visualisation, IEEE, pp. 514–518.

  • Parada, G.A., Ceballos, H.G., Cantu, F.J., & Rodriguez-Aceves, L.(2013). Recommending intra-institutional scientific collaborationthrough coauthorship network visualization. In Proceedings of the2013 workshop on Computational scientometrics: theory&applications - CompSci ’13, ACM Press, New York, NYk, USA, pp. 7–12.

  • Perc, M. (2010). Growth and structure of Slovenia’s scientific collaboration network. Journal of Informetrics, 4(4), 475–482.

    Article  MathSciNet  Google Scholar 

  • Perc, M. (2014). The matthew effect in empirical data. Journal of The Royal Society Interface, 11(98), 20140,378.

    Article  Google Scholar 

  • Perianes-Rodríguez, A., Olmeda-Gómez, C., & Moya-Anegón, F. (2009). Detecting, identifying and visualizing research groups in co-authorship networks. Scientometrics, 82(2), 307–319.

    Article  Google Scholar 

  • Pujari, S.C., Hadgu, A.T., Lex, E., & Jäschke, R. (2015). Social activity versus academic activity: A case study of computer scientists on twitter. In Proceedings of the 15th International Conference on Knowledge Technologies and Data-driven Business, ACM, i-KNOW ’15, pp. 12:1–12:8.

  • Rosvall, M., & Bergstrom, C. T. (2008). Maps of random walks on complex networks reveal community structure. Proceedings of the National Academy of Sciences, 105(4), 1118–1123.

    Article  Google Scholar 

  • Savić, M., Ivanović, M., Radovanović, M., Ognjanović, Z., Pejović, A., & Jakšić Krüger, T. (2014). The structure and evolution of scientific collaboration in Serbian mathematical journals. Scientometrics, 101(3), 1805–1830.

    Article  Google Scholar 

  • Sun, Wj., & Jiang, Ax. (2009). The collaboration network in China’s management science. In 2009 International Conference on Management Science and Engineering, IEEE, pp 40–44.

  • Tomassini, M., & Luthi, L. (2007). Empirical analysis of the evolution of a scientific collaboration network. Physica A: Statistical Mechanics and its Applications, 385(2), 750–764.

    Article  Google Scholar 

  • Velden, T., & Lagoze, C. (2009). Patterns of Collaboration in Co-authorship Networks in Chemistry - Mesoscopic Analysis and Interpretation. In Proceedings of Issi 2009—12th International Conference of the International Society for Scientometrics and Informetrics, Vol. 2 pp 764–775.

  • Wagner, C. S., Horlings, E., Whetsell, T. A., Mattsson, P., & Nordqvist, K. (2015). Do nobel laureates create prize-winning networks? An analysis of collaborative research in physiology or medicine. PLoS One, 10(7), e0134,164.

    Article  Google Scholar 

  • Wang, T., Zhang, Q., Liu, Z., Liu, W., & Wen, D. (2012). On social computing research collaboration patterns: A social network perspective. Frontiers of Computer Science, 6(1), 122–130.

    MathSciNet  Google Scholar 

  • Xiang, D., & Li, H. (2012). Analyzing international scientific collaboration pattern for China by using ESI database. In 2012 IEEE International Conference on Industrial Engineering and Engineering Management, IEEE, pp. 1386–1390.

  • Xu, J. J., Chau, M., & Tan, B. C. Y. (2014). The development of social capital in the collaboration network of information systems scholars. Journal of the Association of Information Systems, 15(12), 835–859.

    Google Scholar 

  • Yan, E., & Ding, Y. (2012). Scholarly network similarities: How bibliographic coupling networks, citation networks, cocitation networks, topical networks, coauthorship networks, and coword networks relate to each other. Journal of the American Society for Information Science and Technology, 63(7), 1313–1326.

    Article  Google Scholar 

  • Yan, E., & Guns, R. (2014). Predicting and recommending collaborations: An author-, institution-, and country-level analysis. Journal of Informetrics, 8(2), 295–309.

    Article  Google Scholar 

  • Yan, E., Ding, Y., & Zhu, Q. (2009). Mapping library and information science in China: a coauthorship network analysis. Scientometrics, 83(1), 115–131.

    Article  Google Scholar 

  • Yoshikane, F., & Kageura, K. (2004). Comparative analysis of coauthorship networks of different domains: The growth and change of networks. Scientometrics, 60(3), 435–446.

    Article  Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge the support received within the OPEN-RES Academic Writing Project 212/2012.

Author information

Authors and Affiliations

  1. Babeş-Bolyai University, Cluj-Napoca, Romania

    Noémi Gaskó, Rodica Ioana Lung & Mihai Alexandru Suciu

Authors
  1. Noémi Gaskó
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rodica Ioana Lung
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mihai Alexandru Suciu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rodica Ioana Lung.

Appendix: Numerical values for the network indices

Appendix: Numerical values for the network indices

See Table 2.

Table 2 Network indices for the constructed networks
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gaskó, N., Lung, R.I. & Suciu, M.A. A new network model for the study of scientific collaborations: Romanian computer science and mathematics co-authorship networks. Scientometrics 108, 613–632 (2016). https://doi.org/10.1007/s11192-016-1968-4

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-016-1968-4

Keywords

Search

Navigation