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Analysis of the evolution and collaboration networks of citizen science scientific publications

Author

Listed:
  • M. Pelacho

    (Universidad de Zaragoza
    Universidad del País Vasco UPV/EHU)

  • G. Ruiz

    (Universidad de Zaragoza)

  • F. Sanz

    (Universidad de Zaragoza)

  • A. Tarancón

    (Universidad de Zaragoza
    Universidad de Zaragoza)

  • J. Clemente-Gallardo

    (Universidad de Zaragoza
    Universidad de Zaragoza
    Universidad de Zaragoza)

Abstract

The term citizen science refers to a broad set of practices developed in a growing number of areas of knowledge and characterized by the active citizen participation in some or several stages of the research process. Definitions, classifications and terminology remain open, reflecting that citizen science is an evolving phenomenon, a spectrum of practices whose classification may be useful but never unique or definitive. The aim of this article is to study citizen science publications in journals indexed by WoS, in particular how they have evolved in the last 20 years and the collaboration networks which have been created among the researchers in that time. In principle, the evolution can be analyzed, in a quantitative way, by the usual tools, such as the number of publications, authors, and impact factor of the papers, as well as the set of different research areas including citizen science as an object of study. But as citizen science is a transversal concept which appears in almost all scientific disciplines, this study becomes a multifaceted problem which is only partially modelled with the usual bibliometric magnitudes. It is necessary to consider new tools to parametrize a set of complementary properties. Thus, we address the study of the citizen science expansion and evolution in terms of the properties of the graphs which encode relations between scientists by studying co-authorship and the consequent networks of collaboration. This approach - not used until now in research on citizen science, as far as we know- allows us to analyze the properties of these networks through graph theory, and complement the existing quantitative research. The results obtained lead mainly to: (a) a better understanding of the current state of citizen science in the international academic system-by countries, by areas of knowledge, by interdisciplinary communities-as an increasingly legitimate expanding methodology, and (b) a greater knowledge of collaborative networks and their evolution, within and between research communities, which allows a certain margin of predictability as well as the definition of better cooperation strategies.

Suggested Citation

  • M. Pelacho & G. Ruiz & F. Sanz & A. Tarancón & J. Clemente-Gallardo, 2021. "Analysis of the evolution and collaboration networks of citizen science scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 225-257, January.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:1:d:10.1007_s11192-020-03724-x
    DOI: 10.1007/s11192-020-03724-x
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    References listed on IDEAS

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    1. R. Álvarez & E. Cahué & J. Clemente-Gallardo & A. Ferrer & D. Íñiguez & X. Mellado & A. Rivero & G. Ruiz & F. Sanz & E. Serrano & A. Tarancón & Y. Vergara, 2015. "Analysis of academic productivity based on Complex Networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 651-672, September.
    2. Florian Heigl & Barbara Kieslinger & Katharina T. Paul & Julia Uhlik & Daniel Dörler, 2019. "Opinion: Toward an international definition of citizen science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 116(17), pages 8089-8092, April.
    3. Abbasi, Alireza & Altmann, Jörn & Hossain, Liaquat, 2011. "Identifying the effects of co-authorship networks on the performance of scholars: A correlation and regression analysis of performance measures and social network analysis measures," Journal of Informetrics, Elsevier, vol. 5(4), pages 594-607.
    4. Yuxiang Zhao & Qinghua Zhu, 2014. "Evaluation on crowdsourcing research: Current status and future direction," Information Systems Frontiers, Springer, vol. 16(3), pages 417-434, July.
    5. Núria Bautista-Puig & Daniela De Filippo & Elba Mauleón & Elías Sanz-Casado, 2019. "Scientific Landscape of Citizen Science Publications: Dynamics, Content and Presence in Social Media," Publications, MDPI, vol. 7(1), pages 1-22, February.
    6. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    7. Clemente-Gallardo, J. & Ferrer, A. & Íñiguez, D. & Rivero, A. & Ruiz, G. & Tarancón, A., 2019. "Do researchers collaborate in a similar way to publish and to develop projects?," Journal of Informetrics, Elsevier, vol. 13(1), pages 64-77.
    8. Franzoni, Chiara & Sauermann, Henry, 2014. "Crowd science: The organization of scientific research in open collaborative projects," Research Policy, Elsevier, vol. 43(1), pages 1-20.
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    Cited by:

    1. Lala Hajibayova & L. P. Coladangelo & Heather A. Soyka, 2021. "Exploring the invisible college of citizen science: questions, methods and contributions," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6989-7003, August.
    2. Egidijus Jurkus & Ramūnas Povilanskas & Julius Taminskas, 2022. "Current Trends and Issues in Research on Biodiversity Conservation and Tourism Sustainability," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    3. Tošić, Aleksandar & Vičič, Jernej, 2021. "Use of Benford's law on academic publishing networks," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Ana C. M. Brito & Filipi N. Silva & Diego R. Amancio, 2023. "Analyzing the influence of prolific collaborations on authors productivity and visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2471-2487, April.

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