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Manifestation of research teams in journal literature: A growth model of papers, authors, collaboration, coauthorship, weak ties, and Lotka's law

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  • Steven A. Morris
  • Michel L. Goldstein

Abstract

This article introduces a team‐based model of researchers in a specialty and investigates the manifestation of such teams in a specialty's literature. The proposed qualitative behavioral model, with its mathematical expression as a growth model, is significant because it simultaneously describes the two phenomena of collaboration and author productivity (Lotka's law) in a specialty. The model is nested: A team process models the creation of research teams and the success‐breeds‐success process of their production of articles, while at a lower level the productivity of authors within teams is also modeled as a success‐breeds‐success process. Interteam collaboration (weak ties) is modeled as random events. This simple growth model is shown to faithfully mimic six network metrics of bipartite article‐author networks. The model is demonstrated on three example article collections from specialties that have a wide range of degree of collaboration: (a) a distance education collection with low collaboration degree, (b) a complex networks collection with typical collaboration degree, and (c) an atrial ablation collection with heavy collaboration degree.

Suggested Citation

  • Steven A. Morris & Michel L. Goldstein, 2007. "Manifestation of research teams in journal literature: A growth model of papers, authors, collaboration, coauthorship, weak ties, and Lotka's law," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(12), pages 1764-1782, October.
  • Handle: RePEc:bla:jamist:v:58:y:2007:i:12:p:1764-1782
    DOI: 10.1002/asi.20661
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    Cited by:

    1. Jin Mao & Yujie Cao & Kun Lu & Gang Li, 2017. "Topic scientific community in science: a combined perspective of scientific collaboration and topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(2), pages 851-875, August.
    2. Yichi Zhang & Zhiliang Dong & Sen Liu & Peixiang Jiang & Cuizhi Zhang & Chao Ding, 2021. "Forecast of International Trade of Lithium Carbonate Products in Importing Countries and Small-Scale Exporting Countries," Sustainability, MDPI, vol. 13(3), pages 1-23, January.
    3. Debabrata Talukdar, 2011. "Patterns of Research Productivity in the Business Ethics Literature: Insights from Analyses of Bibliometric Distributions," Journal of Business Ethics, Springer, vol. 98(1), pages 137-151, January.
    4. Ausloos, M., 2015. "Assessing the true role of coauthors in the h-index measure of an author scientific impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 422(C), pages 136-142.
    5. Haizheng Zhang & Baojun Qiu & Kristinka Ivanova & C. Lee Giles & Henry C. Foley & John Yen, 2010. "Locality and attachedness‐based temporal social network growth dynamics analysis: A case study of evolving nanotechnology scientific collaboration networks," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(5), pages 964-977, May.
    6. Qin Zhang & Juneman Abraham & Hui-Zhen Fu, 2020. "Collaboration and its influence on retraction based on retracted publications during 1978–2017," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 213-232, October.
    7. Bulent Ozel & Hildrun Kretschmer & Theo Kretschmer, 2014. "Co-authorship pair distribution patterns by gender," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 703-723, January.
    8. Hildrun Kretschmer & Donald Beaver & Theo Kretschmer, 2015. "Three-dimensional visualization and animation of emerging patterns by the process of self-organization in collaboration networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(1), pages 87-120, July.
    9. Crockett, David & Downey, Hilary & Fırat, A. Fuat & Ozanne, Julie L. & Pettigrew, Simone, 2013. "Conceptualizing a transformative research agenda," Journal of Business Research, Elsevier, vol. 66(8), pages 1171-1178.
    10. Kretschmer, Hildrun & Beaver, Donald deB. & Ozel, Bulent & Kretschmer, Theo, 2015. "Who is collaborating with whom? Part I. Mathematical model and methods for empirical testing," Journal of Informetrics, Elsevier, vol. 9(2), pages 359-372.
    11. William Latham & Christian Le Bas, 2011. "Causes, Consequences and Dynamics of ‘Complex’ Distributions of Technological Activities: The Case of Prolific Inventors," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 9, Edward Elgar Publishing.
    12. Theresa Velden & Asif-ul Haque & Carl Lagoze, 2010. "A new approach to analyzing patterns of collaboration in co-authorship networks: mesoscopic analysis and interpretation," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(1), pages 219-242, October.
    13. Pär Sundling, 2023. "Author contributions and allocation of authorship credit: testing the validity of different counting methods in the field of chemical biology," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2737-2762, May.

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