A socio-semantic analysis of the research domain on Xylella fastidiosa. Structure and scientific dynamics
- 1. INRAE – UMR LISIS, Marne-la-Vallée, France
- 2. AgroParisTech, Paris, France & INRAE - UMR CBGP, Montpellier, France
- 3. INRAE - UMR CBGP, Montpellier, France
Description
Objective. This poster intends to offer a socio-semantic overall view of the research domain on Xylella fastidiosa as a major quarantine pest with worldwide expansion. This scientometric analysis is applied on a corpus of bibliographic notices, which has been delineated in the Web of Science database with a query based on the reference to Xylella fastidiosa bacteria as a matter of scientific enquiry and as models for phytopathology. Analysis are conducted thanks to the CorTexT Platform, an open science capacity to run various type of textual and network analysis which belong to the RISIS European Infrastructure for science and innovation policies (https://www.risis2.eu/). The purpose of this analysis is to deliver to researchers and policy-maker a retrospective account of the constitution and development of the research domain on Xylella fastidiosa. This account is based on the complementary visions and knowledge of authors’ discipline: computational social science, phytopathology, ecology and genomics.
Methodology. Based on the co-word analysis tradition in Scientometrics (Callon et al., 1983; Waltman, Noyons et al., 2010) and advanced methods in quantitative sciences studies (Cambrosio et al., 2020) our quali-quantitative approach of scientific literature is based on some already well-documented methods of homogeneous and heterogeneous networks analysis and their visualization with Louvain clustering algorithm. We mobilize the portfolio of scripts and algorithms that are proposed on the open platform CorTexT (Barbier & Cointet, 2021). Harnessing a methodology already elaborated in a previous research about ecosystem services (Tancoigne et al., 2014) or Nanotechnology (Kahane et al. 2015) or synthetic biology (Raimbault et al., 2016), we establish the structural composition of this particular research domain with clustering methodology.
Results. A common analysis of fields like co-authors, keywords and cited-reference networks deliver a global and structural account of the domain a first layer of descriptive results. Then, using the projection of a third variable (authors’ countries; journals) with a contingency matrix analysis, we show the existence of national research engagements and almost geopolitics of Xylella fastidiosa research, because of historical investments of scientific activities on the main plant diseases induced by this bacterium. A third result is produced while using bibliographic coupling to cluster the results of a terminological extraction of abstracts; we establish the socio-epistemic features of the domain, and the disciplinary or interdisciplinary lineaments of its composition. This approach enables to deepen the understanding of the research domain despite its polarities on wine grapes, citrus and olive tree. Finally, thanks to evolutionary approach of clustering extracted N-Grams (Chavalarias & Cointet, 2013) we characterised the scientific dynamic of xyl. fastidiosa research domain in the long run.
Conclusion. Our analysis establishes the continuous polarization of scientific exploration through time but also the latest scientific achievements, corresponding to new issues, and the late outbreak in Puglia. This perspective enables to identify the European specificity that is emerging with previous outbreaks.
References
Barbier, M.; Cointet, J.P., (2012). Reconstruction of Socio-Semantic Dynamics in Sciences-Society Networks: Methodology and Epistemology of large textual corpora analysis. Science and Democracy Network, Annual Conference, Paris: 2012.
Buter, R. K., Noyons, E. C., & van Raan, A. F. (2010). Identification of converging research areas using publication and citation data. Research evaluation, 19(1), 19-27.
Callon M., Courtial J., Turner W., Bauin S. (1983). From Translations to Problematic Networks—an Introduction to Co-Word Analysis. Social Science Information. 22(2):191–235.
Cambrosio, A., Cointet, J. P., & Abdo, A. H. (2020). Beyond networks: Aligning qualitative and computational science studies. Quantitative Science Studies, 1(3), 1017-1024.
Chavalarias, D; Cointet, J.P. (2013). Phylomemetic patterns in science evolution - the rise and fall of scientific fields. PloS one, 8 (2), pp. e54847, 2013.
CorText platform (2021). Online documentation. https://www.cortext.net/publications/
Kahane, B., Mogoutov, A., Cointet, J. P., Villard, L., & Laredo, P. (2015). A dynamic query to delineate emergent science and technology: the case of nano science and technology. Content and technical structure of the Nano S&T Dynamics Infrastructure, 47-70. .
Raimbault, Benjamin, Jean-Philippe Cointet, and Pierre-Benoît Joly. "Mapping the emergence of synthetic biology." PloS one 11.9 (2016): e0161522.
Tancoigne, E., Barbier, M., Cointet, J. P., & Richard, G. (2014). The place of agricultural sciences in the literature on ecosystem services. Ecosystem Services, 10, 35–48.
Waltman, L., Van Eck, N. J., & Noyons, E. C. (2010). A unified approach to mapping and clustering of bibliometric networks. Journal of informetrics, 4(4), 629-635.
Notes
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Additional details
Subjects
- Xylella
- http://id.agrisemantics.org/gacs/C20262
- Network analysis
- http://id.agrisemantics.org/gacs/C24826