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Joint estimation of non-parametric transitivity and preferential attachment functions in scientific co-authorship networks

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  • Inoue, Masaaki
  • Pham, Thong
  • Shimodaira, Hidetoshi

Abstract

We propose a statistical method for estimating the non-parametric transitivity and preferential attachment functions simultaneously in a growing network, in contrast to conventional methods that either estimate each function in isolation or assume a certain functional form for these. Our model is demonstrated to exhibit a good fit to two real-world co-authorship networks and can illuminate several intriguing details of the preferential attachment and transitivity phenomena that would be unavailable under traditional methods. Moreover, we introduce a method for quantifying the amount of contributions of these phenomena in the growth process of a network based on the probabilistic dynamic process induced by the model formula. By applying this method, we found that transitivity dominated preferential attachment in both co-authorship networks. This suggests the importance of indirect relations in scientific creative processes. The proposed method is implemented in the R package FoFaF.

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  • Inoue, Masaaki & Pham, Thong & Shimodaira, Hidetoshi, 2020. "Joint estimation of non-parametric transitivity and preferential attachment functions in scientific co-authorship networks," Journal of Informetrics, Elsevier, vol. 14(3).
    • Handle: RePEc:eee:infome:v:14:y:2020:i:3:s175115771930269x
    DOI: 10.1016/j.joi.2020.101042
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    as
    1. Hunter D.R. & Lange K., 2004. "A Tutorial on MM Algorithms," The American Statistician, American Statistical Association, vol. 58, pages 30-37, February.
    2. Lutz Bornmann, 2017. "Is collaboration among scientists related to the citation impact of papers because their quality increases with collaboration? An analysis based on data from F1000Prime and normalized citation scores," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 1036-1047, April.
    3. Staša Milojević, 2010. "Modes of collaboration in modern science: Beyond power laws and preferential attachment," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(7), pages 1410-1423, July.
    4. Hunter, David R. & Goodreau, Steven M. & Handcock, Mark S., 2008. "Goodness of Fit of Social Network Models," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 248-258, March.
    5. Staša Milojević, 2010. "Modes of collaboration in modern science: Beyond power laws and preferential attachment," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(7), pages 1410-1423, July.
    6. Wang, Mingyang & Yu, Guang & Yu, Daren, 2008. "Measuring the preferential attachment mechanism in citation networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(18), pages 4692-4698.
    7. Thong Pham & Paul Sheridan & Hidetoshi Shimodaira, 2015. "PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-18, September.
    8. David Liben‐Nowell & Jon Kleinberg, 2007. "The link‐prediction problem for social networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(7), pages 1019-1031, May.
    9. Joshua Lospinoso & Michael Schweinberger & Tom Snijders & Ruth Ripley, 2011. "Assessing and accounting for time heterogeneity in stochastic actor oriented models," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 5(2), pages 147-176, July.
    10. Luka Kronegger & Franc Mali & Anuška Ferligoj & Patrick Doreian, 2012. "Collaboration structures in Slovenian scientific communities," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 631-647, February.
    11. D. S. Callaway & J. E. Hopcroft & J. M. Kleinberg & M. E. J. Newman & S. H. Strogatz, 2001. "Are Randomly Grown Graphs Really Random?," Working Papers 01-05-025, Santa Fe Institute.
    12. Vincent Larivière & Yves Gingras & Cassidy R. Sugimoto & Andrew Tsou, 2015. "Team size matters: Collaboration and scientific impact since 1900," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(7), pages 1323-1332, July.
    13. Mikhail V. Simkin & Vwani P. Roychowdhury, 2007. "A mathematical theory of citing," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(11), pages 1661-1673, September.
    14. Guillermo Armando Ronda-Pupo & Thong Pham, 2018. "The evolutions of the rich get richer and the fit get richer phenomena in scholarly networks: the case of the strategic management journal," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 363-383, July.
    15. Csárdi, Gábor & Strandburg, Katherine J. & Zalányi, László & Tobochnik, Jan & Érdi, Péter, 2007. "Modeling innovation by a kinetic description of the patent citation system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(2), pages 783-793.
    16. Anuška Ferligoj & Luka Kronegger & Franc Mali & Tom A. B. Snijders & Patrick Doreian, 2015. "Scientific collaboration dynamics in a national scientific system," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 985-1012, September.
    17. Antonio Zinilli, 2016. "Competitive project funding and dynamic complex networks: evidence from Projects of National Interest (PRIN)," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 633-652, August.
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