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Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study

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  • David Chavalarias

    (Team Complex Systems, Adaptive Rationality and Social Cognition, Ecole Polytechnique)

  • Jean-Philippe Cointet

    (INRA)

Abstract

We propose new methods to detect paradigmatic fields through simple statistics over a scientific content database. We propose an asymmetric paradigmatic proximity metric between terms which provide insight into hierarchical structure of scientific activity and test our methods on a case study with a database made of several millions of resources. We also propose overlapping categorization to describe paradigmatic fields as sets of terms that may have several different usages. Terms can also be dynamically clustered providing a high-level description of the evolution of the paradigmatic fields.

Suggested Citation

  • David Chavalarias & Jean-Philippe Cointet, 2008. "Bottom-up scientific field detection for dynamical and hierarchical science mapping, methodology and case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(1), pages 37-50, April.
    • Handle: RePEc:spr:scient:v:75:y:2008:i:1:d:10.1007_s11192-007-1825-6
    DOI: 10.1007/s11192-007-1825-6
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    References listed on IDEAS

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    1. Peter van den Besselaar & Gaston Heimeriks, 2006. "Mapping research topics using word-reference co-occurrences: A method and an exploratory case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(3), pages 377-393, September.
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    4. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. I. Structural aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 233-251, May.
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    6. Robert R. Braam & Henk F. Moed & Anthony F. J. van Raan, 1991. "Mapping of science by combined co‐citation and word analysis. II: Dynamical aspects," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 42(4), pages 252-266, May.
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    Cited by:

    1. Matteo Lascialfari & Marie-Benoît Magrini & Guillaume Cabanac, 2022. "Unpacking research lock-in through a diachronic analysis of topic cluster trajectories in scholarly publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6165-6189, November.
    2. Chavalarias David & Beatrice De Gelder & Guido Caldarelli & Melanie Dulong de Rosnay & Antonio A. Casilli & Alexandre Delanoë & Luisa Fassi & Divina Frau-Meigs & Bertrand Jouve & Andrzej Nowak & Vícto, 2023. "Toward a Research Agenda on Digital Media and Humanity Well-Being," Working Papers hal-04091733, HAL.
    3. Bettencourt, Luís M.A. & Kaiser, David I. & Kaur, Jasleen, 2009. "Scientific discovery and topological transitions in collaboration networks," Journal of Informetrics, Elsevier, vol. 3(3), pages 210-221.
    4. Vilker Zucolotto Pessin & Luciana Harue Yamane & Renato Ribeiro Siman, 2022. "Smart bibliometrics: an integrated method of science mapping and bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3695-3718, June.
    5. Sun, Xiaoling & Ding, Kun & Lin, Yuan, 2016. "Mapping the evolution of scientific fields based on cross-field authors," Journal of Informetrics, Elsevier, vol. 10(3), pages 750-761.
    6. Li, Xianghua & Wang, Zhen & Gao, Chao & Shi, Lei, 2017. "Reasoning human emotional responses from large-scale social and public media," Applied Mathematics and Computation, Elsevier, vol. 310(C), pages 182-193.
    7. David Chavalarias & Quentin Lobbé & Alexandre Delanoë, 2022. "Draw me Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 545-575, January.
    8. Chavalarias David & Beatrice De Gelder & Guido Caldarelli & Melanie Dulong de Rosnay & Antonio A. Casilli & Alexandre Delanoë & Luisa Fassi & Divina Frau-Meigs & Bertrand Jouve & Andrzej Nowak & Vícto, 2023. "Toward a Research Agenda on Digital Media and Humanity Well-Being," SciencePo Working papers Main hal-04091733, HAL.

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