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Computer science research: more production, less productivity

Author

Listed:
  • José María Cavero

    (Universidad Rey Juan Carlos)

  • Belén Vela

    (Universidad Rey Juan Carlos)

  • Paloma Cáceres

    (Universidad Rey Juan Carlos)

Abstract

It is commonly accepted that scientific research or, more precisely, the number of scientific publications, in computer science has greatly increased over the last few years. The reason would appear to be the pressure to publish, coined by the expression ”Publish or perish”, which is, among other things, necessary for promotions and applications for grants or projects. In this paper we have conducted a study that covers computer science publications from 1936 to 2010 in order to quantify this increase in publications regarding computing research. We have considered the computing conferences and journals available in the DBLP computer science bibliography (DBLP 2013) database, including more than 1.5 million papers, and more than 4 million authors (more than 900,000 different people), corresponding to about 1,000 different journals and 3,000 different conferences and workshops. Our study confirms and quantifies these increases with regard to the number of papers, number of authors, number of papers per author, etc. However, it also reaches a surprising conclusion: the real productivity of researchers has decreased throughout history. The reason for this decrease is the average number of authors per paper, which has grown significantly and is currently three.

Suggested Citation

  • José María Cavero & Belén Vela & Paloma Cáceres, 2014. "Computer science research: more production, less productivity," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2103-2111, March.
    • Handle: RePEc:spr:scient:v:98:y:2014:i:3:d:10.1007_s11192-013-1178-2
    DOI: 10.1007/s11192-013-1178-2
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    References listed on IDEAS

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    1. Hendrik P. van Dalen & Kène Henkens, 2012. "Intended and unintended consequences of a publish‐or‐perish culture: A worldwide survey," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(7), pages 1282-1293, July.
    2. Derek R. Smith, 2012. "Impact factors, scientometrics and the history of citation-based research," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 419-427, August.
    3. Daniele Fanelli, 2010. "Do Pressures to Publish Increase Scientists' Bias? An Empirical Support from US States Data," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-7, April.
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    Cited by:

    1. João M. Fernandes & Miguel P. Monteiro, 2017. "Evolution in the number of authors of computer science publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(2), pages 529-539, February.
    2. Jesus Palomo & Cristina Figueroa-Domecq & Pilar Laguna, 2017. "Women, peace and security state-of-art: a bibliometric analysis in social sciences based on SCOPUS database," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 123-148, October.
    3. Camil Demetrescu & Irene Finocchi & Andrea Ribichini & Marco Schaerf, 2022. "On computer science research and its temporal evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4913-4938, August.
    4. Guillaume Cabanac & Gilles Hubert & Béatrice Milard, 2015. "Academic careers in Computer Science: continuance and transience of lifetime co-authorships," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 135-150, January.
    5. José María Cavero & Belén Vela & Paloma Cáceres & Carlos Cuesta & Almudena Sierra-Alonso, 2015. "The evolution of female authorship in computing research," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 85-100, April.
    6. Kim, Jinseok & Diesner, Jana, 2015. "The effect of data pre-processing on understanding the evolution of collaboration networks," Journal of Informetrics, Elsevier, vol. 9(1), pages 226-236.

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