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Mapping the dynamics of research networks in ecology and evolution using co-citation analysis (1975–2014)

Author

Listed:
  • Denis Réale

    (Université du Québec à Montréal)

  • Mahdi Khelfaoui

    (Université du Québec à Montréal)

  • Pierre-Olivier Montiglio

    (Université du Québec à Montréal)

  • Yves Gingras

    (Université du Québec à Montréal)

Abstract

In this paper we used a co-citation network analysis to quantify and illustrate the dynamic patterns of research in ecology and evolution over 40 years (1975–2014). We addressed questions about the historical patterns of development of these two fields. Have ecology and evolution always formed a coherent body of literature? What dominant ideas have motivated research activity in these two fields? How long have these ideas attracted the attention of researchers? Contrary to what was expected, we did not observe any trend towards a stronger integration of ecology and evolution into one big cluster that would suggest the existence of a single community. Three main bodies of literature have stayed relatively stable over time: population/community ecology, evolutionary ecology, and population/quantitative genetics. Other fields have disappeared, emerged or mutated over time. Besides, research organization has shifted from a taxon-oriented structure to a concept-oriented one over the years, with researchers working on the same topics but on different taxa showing more interactions.

Suggested Citation

  • Denis Réale & Mahdi Khelfaoui & Pierre-Olivier Montiglio & Yves Gingras, 2020. "Mapping the dynamics of research networks in ecology and evolution using co-citation analysis (1975–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1361-1385, March.
  • Handle: RePEc:spr:scient:v:122:y:2020:i:3:d:10.1007_s11192-019-03340-4
    DOI: 10.1007/s11192-019-03340-4
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    References listed on IDEAS

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    1. Moerchel, Alexander & Tietze, Frank & Urmetzer, Florian, 2023. "Visualising dynamics in innovation ecosystems: A new method and demonstration in the commercial aircraft MRO ecosystem," Technovation, Elsevier, vol. 128(C).
    2. Xinyuan Zhang & Qing Xie & Chaemin Song & Min Song, 2022. "Mining the evolutionary process of knowledge through multiple relationships between keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 2023-2053, April.

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