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Understanding and modeling diverse scientific careers of researchers

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  • Chakraborty, Tanmoy
  • Tammana, Vihar
  • Ganguly, Niloy
  • Mukherjee, Animesh

Abstract

This paper analyzes the diverse scientific careers of researchers in order to understand the key factors that could lead to a successful career. Essentially, we intend to answer some specific questions pertaining to a researcher's scientific career – What are the local and the global dynamics regulating a researcher's decision to select a new field of research at different points of her entire career? What are the suitable quantitative indicators to measure the diversity of a researcher's scientific career? We propose two entropy-based metrics to measure a researcher's choice of research topics. Experiments with large computer science bibliographic dataset reveal that there is a strong correlation between the diversity of the career of a researcher and her success in scientific research in terms of the number of citations. We observe that while most of the researchers are biased toward either adopting diverse research fields or concentrating on very few fields, a majority of the prominent researchers tend to follow a typical “scatter-gather” policy – although their entire careers are immensely diverse with different types of fields selected at different time periods, they remain focused primarily in at most one or two fields at any particular time point of their career. Finally, we propose a stochastic model which, quite accurately, mimics the notion of field selection process observed in the real publication dataset.

Suggested Citation

  • Chakraborty, Tanmoy & Tammana, Vihar & Ganguly, Niloy & Mukherjee, Animesh, 2015. "Understanding and modeling diverse scientific careers of researchers," Journal of Informetrics, Elsevier, vol. 9(1), pages 69-78.
  • Handle: RePEc:eee:infome:v:9:y:2015:i:1:p:69-78
    DOI: 10.1016/j.joi.2014.11.008
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    References listed on IDEAS

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    Cited by:

    1. Abramo, Giovanni & D'Angelo, Ciriaco Andrea & Di Costa, Flavia, 2019. "Diversification versus specialization in scientific research: Which strategy pays off?," Technovation, Elsevier, vol. 82, pages 51-57.
    2. Katchanov, Yurij L. & Markova, Yulia V. & Shmatko, Natalia A., 2023. "Empirical demonstration of the Matthew effect in scientific research careers," Journal of Informetrics, Elsevier, vol. 17(4).
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2018. "The effects of gender, age and academic rank on research diversification," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 373-387, February.
    4. Manuel Goyanes & Márton Demeter & Zicheng Cheng & Homero Gil Zúñiga, 2022. "Measuring publication diversity among the most productive scholars: how research trajectories differ in communication, psychology, and political science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3661-3682, June.
    5. Mike Thelwall, 2016. "Interpreting correlations between citation counts and other indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 337-347, July.
    6. Andrea Bonaccorsi & Nicola Melluso & Francesco Alessandro Massucci, 2022. "Exploring the antecedents of interdisciplinarity at the European Research Council: a topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 6961-6991, December.
    7. Elmira Janavi & Mohammad Javad Mansourzadeh & Mojgan Samandar Ali Eshtehardi, 2020. "A methodology for developing scientific diversification strategy of countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2229-2264, December.

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