IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v75y2008i3d10.1007_s11192-007-1888-4.html
   My bibliography  Save this article

Population modeling of the emergence and development of scientific fields

Author

Listed:
  • Luís M. A. Bettencourt

    (Theoretical Division
    Santa Fe Institute)

  • David I. Kaiser

    (Massachusetts Institute of Technology)

  • Jasleen Kaur

    (Theoretical Division
    Indiana University)

  • Carlos Castillo-Chávez

    (Arizona State University)

  • David E. Wojick

    (Office of Scientific and Technical Information)

Abstract

We analyze the temporal evolution of emerging fields within several scientific disciplines in terms of numbers of authors and publications. From bibliographic searches we construct databases of authors, papers, and their dates of publication. We show that the temporal development of each field, while different in detail, is well described by population contagion models, suitably adapted from epidemiology to reflect the dynamics of scientific interaction. Dynamical parameters are estimated and discussed to reflect fundamental characteristics of the field, such as time of apprenticeship and recruitment rate. We also show that fields are characterized by simple scaling laws relating numbers of new publications to new authors, with exponents that reflect increasing or decreasing returns in scientific productivity.

Suggested Citation

  • Luís M. A. Bettencourt & David I. Kaiser & Jasleen Kaur & Carlos Castillo-Chávez & David E. Wojick, 2008. "Population modeling of the emergence and development of scientific fields," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 495-518, June.
  • Handle: RePEc:spr:scient:v:75:y:2008:i:3:d:10.1007_s11192-007-1888-4
    DOI: 10.1007/s11192-007-1888-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-007-1888-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-007-1888-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Tibor Braun & Sándor Zsindely & Ildikó Dióspatonyi & Erika Zádor, 2007. "Gatekeeping patterns in nano-titled journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(3), pages 651-667, March.
    2. Bettencourt, Luís M.A. & Cintrón-Arias, Ariel & Kaiser, David I. & Castillo-Chávez, Carlos, 2006. "The power of a good idea: Quantitative modeling of the spread of ideas from epidemiological models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 513-536.
    3. Lynne G. Zucker & Michael R. Darby, 2005. "Socio-economic Impact of Nanoscale Science: Initial Results and NanoBank," NBER Working Papers 11181, National Bureau of Economic Research, Inc.
    4. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lambiotte, R. & Panzarasa, P., 2009. "Communities, knowledge creation, and information diffusion," Journal of Informetrics, Elsevier, vol. 3(3), pages 180-190.
    2. Bettencourt, Luís M.A. & Kaiser, David I. & Kaur, Jasleen, 2009. "Scientific discovery and topological transitions in collaboration networks," Journal of Informetrics, Elsevier, vol. 3(3), pages 210-221.
    3. Kiss, Istvan Z. & Broom, Mark & Craze, Paul G. & Rafols, Ismael, 2010. "Can epidemic models describe the diffusion of topics across disciplines?," Journal of Informetrics, Elsevier, vol. 4(1), pages 74-82.
    4. De Martino, Giuseppe & Spina, Serena, 2015. "Exploiting the time-dynamics of news diffusion on the Internet through a generalized Susceptible–Infected model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 634-644.
    5. Andreas Bjurström & Merritt Polk, 2011. "Climate change and interdisciplinarity: a co-citation analysis of IPCC Third Assessment Report," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 525-550, June.
    6. Citron, Daniel T. & Way, Samuel F., 2018. "Network assembly of scientific communities of varying size and specificity," Journal of Informetrics, Elsevier, vol. 12(1), pages 181-190.
    7. Patrick Herron & Aashish Mehta & Cong Cao & Timothy Lenoir, 2016. "Research diversification and impact: the case of national nanoscience development," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 629-659, November.
    8. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    9. Wang, Haiying & Moore, Jack Murdoch & Wang, Jun & Small, Michael, 2021. "The distinct roles of initial transmission and retransmission in the persistence of knowledge in complex networks," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    10. Jianhua Hou, 2017. "Exploration into the evolution and historical roots of citation analysis by referenced publication year spectroscopy," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1437-1452, March.
    11. van Eck, N.J.P. & Waltman, L., 2009. "How to Normalize Co-Occurrence Data? An Analysis of Some Well-Known Similarity Measures," ERIM Report Series Research in Management ERS-2009-001-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    12. Ying Huang & Wolfgang Glänzel & Lin Zhang, 2021. "Tracing the development of mapping knowledge domains," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6201-6224, July.
    13. Perianes-Rodriguez, Antonio & Ruiz-Castillo, Javier, 2017. "A comparison of the Web of Science and publication-level classification systems of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 32-45.
    14. Esther García-Carpintero & Begoña Granadino & Luis M. Plaza, 2010. "The representation of nationalities on the editorial boards of international journals and the promotion of the scientific output of the same countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(3), pages 799-811, September.
    15. Jimi Adams & Ryan Light, 2014. "Mapping Interdisciplinary Fields: Efficiencies, Gaps and Redundancies in HIV/AIDS Research," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-13, December.
    16. Rosa Rodriguez-Sánchez & J. A. García & J. Fdez-Valdivia, 2014. "Evolutionary games between subject categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 869-888, October.
    17. Sidemar Cezario & Thiago Marques & Rafael Pinto & Juciano Lacerda & Lyrene Silva & Thaisa Santos Lima & Orivaldo Santana & Anna Giselle Ribeiro & Agnaldo Cruz & Ana Claudia Araújo & Angélica Espinosa , 2022. "Similarity Analysis in Understanding Online News in Response to Public Health Crisis," IJERPH, MDPI, vol. 19(24), pages 1-14, December.
    18. Nwaibeh, E.A. & Chikwendu, C.R., 2023. "A deterministic model of the spread of scam rumor and its numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 111-129.
    19. Amin Mazloumian, 2012. "Predicting Scholars' Scientific Impact," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-5, November.
    20. Chen, Xiaoyan & Liu, Yisheng, 2020. "Visualization analysis of high-speed railway research based on CiteSpace," Transport Policy, Elsevier, vol. 85(C), pages 1-17.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:75:y:2008:i:3:d:10.1007_s11192-007-1888-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.