Abstract
This study is aim to determine significant changes and trends in neuroscience literature concerning Medical Subject Headings (MeSH) from 2000 to 2017. This article encourage researchers to help identify perhaps the most influential studies and combine detailed evidence into study-considered higher education. To our knowledge and understanding, almost no study found alterations in neuroscientific literature during the last decade in Turkey. In this study, the main aim is to present a science map of “Neuroscience literature”, is a growing field of research in Turkey. This study explores maps of scientific publications related to research in Neuroscience that accuracy of clustering and classification of scientific fields is enhanced by incorporation of algorithms and main bibliometric analysis. Data were extracted from the Web of Science (WoS) database and matched with PubMed database via PubMed ID. Only articles published in journals classified under the Web of science category (WC) “Neurosciences” over the period of interest were included. MeSH term, abstract fields and references of each included publication were extracted and analyzed via Bibliotools software to identify recurring terms with high relative citation scores. MeSH term maps were produced for publications over the study period to illustrate the extent of co-occurrence, and the impact of terms was evaluated based on their relative citation scores. To further describe the recent research priority or “hot spots,” MeSH terms, Journals, authors with the highest relative citation scores were identified annually. We focused on two successive periods: in 2000–2007 there are 1807 publications in WoS and 1510 publications in the bibliographic coupling (BC). 1291 publications gathered in 16 top clusters and 1103 publications gathered in 47 subtop clusters. In 2008–2017: there are 3668 publications in WoS, 3312 publications in the BC network. 2924 publications gathered in 20 top clusters and 2500 publications gathered in 87 subtop clusters. In the corpus description interface, interactive tools are used to explore the nature of the two studied corpora by listing MeSH terms, references, categories, authors, journals, institutions, countries, etc. by frequency of use. In the BC interface, interactive tools are used to explore the multiple dimensions of the topics (or clusters) unveiled by our analysis. The two periods were studied independently, and although we use matching colors for topics that obviously correspond to one another from one-time period to another. We focused on two successive periods: in 2000–2007 there are 1807 publications in WoS and 1510 publications in the bibliographic coupling (BC). 1291 publications gathered in 16 top clusters and 1103 publications gathered in 47 subtop clusters. In 2008–2017: there are 3668 publications in WoS, 3312 publications in the BC network. 2924 publications gathered in 20 top clusters and 2500 publications gathered in 87 subtop clusters. In the corpus description interface, interactive tools are used to explore the nature of the two studied corpora by listing MeSH terms, references, categories, authors, journals, institutions, countries, etc. by frequency of use. In the BC interface, interactive tools are used to explore the multiple dimensions of the topics (or clusters) unveiled by our analysis. The two periods were studied independently, and although we use matching colors for topics that obviously correspond to one another from one-time period to another. In recent years, because of an increase in the size of the aging population, the trend of neuroscience research has been increased. Neuroscience is currently the fastest growing area in basic scientific research. This paper gives a contemporary summary to scientists and medical professionals interested in research and innovation in this field. Furthermore, Neuroscience research plays a vital role in the development of instruments categories of emerging medical technology. It is clear that this paper helps researchers who study the neuroscience to recognize significant changes and trends in the literature of neurosciences.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bala, A., & Gupta, B. M. (2010). Mapping of Indian neuroscience research: A scientometric analysis of research output during 1999–2008. Neurology India,58(1), 35.
Berardelli, A., Barberini, I., Defazio, G., Mancardi, G. L., & Messina, C. (2005). Neurological research in Italy in 2003 and 2004. Neurological Sciences,26(4), 189–193.
Boyack, K. W., & Klavans, R. (2010). Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately? The Journal of the Association for Information Science and Technology,61(12), 2389404.
Braun, T., Glänzel, W., & Grupp, H. (1995). The scientometric weight of 50 nations in 27 science areas, 1989–1993. Part I. All fields combined, mathematics, engineering, chemistry and physics. Scientometrics,33(3), 263–293.
Buchan, A. M., Jurczyk, E., Isserlin, R., & Bader, G. D. (2016). Global neuroscience and mental health research: A bibliometrics case study. Scientometrics,109(1), 515–531.
Cobo, M. J., López-Herrera, A. G., Herrera-Viedma, E., & Herrera, F. (2011). Science mapping software tools: Review, analysis, and cooperative study among tools. Journal of the American Society for Information Science and Technology,62(7), 1382–1402.
De Bellis, N. (2009). Bibliometrics and citation analysis: From the science citation index to cybermetrics. Lanham: Scarecrow Press.
Dorta-Contreras, A. J., Arencibia-Jorge, R., Marti-Lahera, Y., & Araujo-Ruiz, J. A. (2007). Productivity and visibility of Cuban neuroscientists: bibliometric study of the period 2001–2005. Revista de neurologia,47(7), 355–360.
Glänzel, W., & Schubert, A. (2003). A new classification scheme of science fields and subfields designed for scientometric evaluation purposes. Scientometrics,56(3), 357–367.
Gomez, I., Sanz, E., & Méndez, A. (1990). Utility of bibliometric analysis for research policy: A case study of Spanish research in neuroscience. Research Policy,19(5), 457–466.
Grauwin, S., & Jensen, P. (2011). Mapping scientific institutions. Scientometrics,89(3), 943–954.
Heersmink, R., van den Hoven, J., van Eck, N. J., & van den Berg, J. (2011). Bibliometric mapping of computer and information ethics. Ethics and Information Technology,13, 241–249. https://doi.org/10.1007/s10676-011-9273-7.
Hoppen, N. H. F., de Souza, C. D., De Filippo, D., de Souza Vanz, S. A., & Sanz-Casado, E. (2016). Brazilian Neuroscience research areas: a bibliometric analysis from 2006 to 2013. Informação and Sociedade: Estudos,26(3), 2016.
Hoppen, N. H. F., & de Souza Vanz, S. A. (2016). Neurosciences in Brazil: A bibliometric study of main characteristics, collaboration and citations. Scientometrics,109(1), 121–141.
Kessler, M. M. (1963). Bibliographic coupling between scientific papers. American Documentation,14(1), 10–25.
López-Muñoz, F., Boya, J., & Alamo, C. (2006). Neuron theory, the cornerstone of neuroscience, on the centenary of the Nobel Prize award to Santiago Ramón y Cajal. Brain Research Bulletin,70(4–6), 391–405.
Mela, G. S., & Mancardi, G. L. (2002). Neurological research in Europe, as assessed with a four-year overview of neurological science international journals. Journal of Neurology,249(4), 390–395.
Pritchard, A. (1969). Statistical bibliography or bibliometrics. Journal of documentation,25(4), 348–349.
Shahabuddin, S. M. (2013). Mapping neuroscience research in India–a bibliometric approach. Current Science,104(12), 1619–1626.
Sharifi, V., Rahimi Movaghar, A., Mohammadi, M. R., Goodarzi, R. R., Izadian, E. S., Farhoudian, A., et al. (2008). Analysis of mental health research in the Islamic Republic of Iran over 3 decades: a scientometric study. In W. Hadley (Ed.), 2016 ggplot2: Elegant graphics for data analysis. New York: Springer.
Xu, W., Chen, Y. Z., & Shen, Z. C. (2003). Neuroscience output of China: A MEDLINE-based bibliometric study. Scientometrics,57(3), 399–409.
Acknowledgements
Funding was provided by Türkiye Bilimsel ve Teknolojik Araştirma Kurumu (Grant No. 1059B141601141)
Author information
Authors and Affiliations
Corresponding author
Appendix
Appendix
See Table 5.
Rights and permissions
About this article
Cite this article
Kocak, M., García-Zorita, C., Marugán-Lázaro, S. et al. Mapping and clustering analysis on neuroscience literature in Turkey: a bibliometric analysis from 2000 to 2017. Scientometrics 121, 1339–1366 (2019). https://doi.org/10.1007/s11192-019-03259-w
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11192-019-03259-w