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On time-varying collaboration networks

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  • Viana, Matheus P.
  • Amancio, Diego R.
  • da F. Costa, Luciano

Abstract

The patterns of scientific collaboration have been frequently investigated in terms of complex networks without reference to time evolution. In the present work, we derive collaborative networks (from the arXiv repository) parameterized along time. By defining the concept of affine group, we identify several interesting trends in scientific collaboration, including the fact that the average size of the affine groups grows exponentially, while the number of authors increases as a power law. We were therefore able to identify, through extrapolation, the possible date when a single affine group is expected to emerge. Characteristic collaboration patterns were identified for each researcher, and their analysis revealed that larger affine groups tend to be less stable.

Suggested Citation

  • Viana, Matheus P. & Amancio, Diego R. & da F. Costa, Luciano, 2013. "On time-varying collaboration networks," Journal of Informetrics, Elsevier, vol. 7(2), pages 371-378.
    • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:371-378
    DOI: 10.1016/j.joi.2012.12.005
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    References listed on IDEAS

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    5. Amancio, Diego Raphael & Oliveira, Osvaldo Novais & da Fontoura Costa, Luciano, 2012. "Three-feature model to reproduce the topology of citation networks and the effects from authors’ visibility on their h-index," Journal of Informetrics, Elsevier, vol. 6(3), pages 427-434.
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

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    3. Corrêa Jr., Edilson A. & Silva, Filipi N. & da F. Costa, Luciano & Amancio, Diego R., 2017. "Patterns of authors contribution in scientific manuscripts," Journal of Informetrics, Elsevier, vol. 11(2), pages 498-510.
    4. Zhang, Dayong & Men, Hao & Zhang, Zhaoxin, 2024. "Assessing the stability of collaboration networks: A structural cohesion analysis perspective," Journal of Informetrics, Elsevier, vol. 18(1).
    5. Ana C. M. Brito & Filipi N. Silva & Diego R. Amancio, 2023. "Analyzing the influence of prolific collaborations on authors productivity and visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2471-2487, April.
    6. Sergi Lozano & Xosé-Pedro Rodríguez & Alex Arenas, 2014. "Atapuerca: evolution of scientific collaboration in an emergent large-scale research infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1505-1520, February.
    7. Shen, Ai-Zhong & Guo, Jin-Li & Wu, Guo-Lin & Jia, Shu-Wei, 2018. "The agglomeration phenomenon influence on the scaling law of the scientific collaboration system," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 461-467.
    8. Wang, Haiying & Wang, Jun & Small, Michael & Moore, Jack Murdoch, 2019. "Review mechanism promotes knowledge transmission in complex networks," Applied Mathematics and Computation, Elsevier, vol. 340(C), pages 113-125.
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    11. Vicente Prado-Gascó & María del Carmen Giménez-Espert & Hans De Witte, 2021. "Job Insecurity in Nursing: A Bibliometric Analysis," IJERPH, MDPI, vol. 18(2), pages 1-13, January.
    12. Mayra Z Rodriguez & Cesar H Comin & Dalcimar Casanova & Odemir M Bruno & Diego R Amancio & Luciano da F Costa & Francisco A Rodrigues, 2019. "Clustering algorithms: A comparative approach," PLOS ONE, Public Library of Science, vol. 14(1), pages 1-34, January.
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