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Does the human capital of teams of natural science authors predict citation frequency?

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  • Paul F. Skilton

    (Arizona State University-Polytechnic)

Abstract

This study examines the relationship between citation frequency and the human capital of teams of authors. Analysis of a random sample of articles published in top natural science journals shows that articles co-authored by teams including frequently cited scholars and teams whose members have diverse disciplinary backgrounds have greater citation frequency. The institutional prestige, the percentage of team members at U. S. institutions and the variety of disciplines represented by team member backgrounds do not influence citation frequency. The study introduces a method for evaluating the extent of multidisciplinarity that accounts for the relatedness of disciplines or authors.

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  • Paul F. Skilton, 2009. "Does the human capital of teams of natural science authors predict citation frequency?," Scientometrics, Springer;Akadémiai Kiadó, vol. 78(3), pages 525-542, March.
    • Handle: RePEc:spr:scient:v:78:y:2009:i:3:d:10.1007_s11192-007-1953-z
    DOI: 10.1007/s11192-007-1953-z
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    Cited by:

    1. Iman Tahamtan & Askar Safipour Afshar & Khadijeh Ahamdzadeh, 2016. "Factors affecting number of citations: a comprehensive review of the literature," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1195-1225, June.
    2. Christopher McCarty & James W. Jawitz & Allison Hopkins & Alex Goldman, 2013. "Predicting author h-index using characteristics of the co-author network," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 467-483, August.
    3. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "The relationship between the number of authors of a publication, its citations and the impact factor of the publishing journal: Evidence from Italy," Journal of Informetrics, Elsevier, vol. 9(4), pages 746-761.
    4. Leo Egghe & Raf Guns & Ronald Rousseau, 2013. "Measuring co-authors’ contribution to an article’s visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 55-67, April.
    5. Winnink, J.J. & Tijssen, Robert J.W. & van Raan, A.F.J., 2019. "Searching for new breakthroughs in science: How effective are computerised detection algorithms?," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 673-686.

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