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Bibliometric Analysis of Publications from Web of Science Affiliated to Health Sciences University from 2017-2019.
Artículo | IMSEAR | ID: sea-214955
ABSTRACT
Bibliometrics is the use of statistical methods for analysing books, articles, and other publications. It is useful to analyse the research impact, assess the quality of research using quantitative and qualitative measures, describe patterns of publication, determine the influence of writers, describe the relationship between different writers or researches. This study was conducted to evalute the number and trends of materials affiliated to Health Sciences University published in Web of Science indexed journals.METHODSThis was a retrospective observational study. The Web of Science database was accessed through institutional Login and all published materials affiliated to Health Sciences University were searched. The file of all searched materials was exported in BibTex format, which was fed to R-Studio Application after installing the Bibliometrics package. Imported data was downloaded and bibliographic data frame was created. Basic information of publications was recorded including the number of citations, citation density, journals, publication year, authors, institution and country of origin. Results were summarized using descriptive statistics.RESULTSBibliometric analysis of publications affiliated to Health Sciences University between 2017 to 2019 generated a list of 182 articles from 75 sources which included 180 Journal Articles and 2 articles in Book Chapters. Highest number of publications were 82 in the year 2019 followed by 51 in 2017 and 49 in 2018. The Annual Percentage Growth Rate of Scientific Productions was 26.8. The publications showed total 2170 authors of which 09 were authors of ‘single-authored documents’ and 2163 were authors of ‘multi-authored documents’. The Collaboration Index of all published materials was 12.5.CONCLUSIONSThis analysis reflects on the historical perspectives of Health Sciences University publications and its progress in Web of Science indexed Scientific Medical Literature database.

Texto completo: Disponible Índice: IMSEAR (Asia Sudoriental) Tipo de estudio: Estudio observacional / Investigación cualitativa Año: 2020 Tipo del documento: Artículo

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Texto completo: Disponible Índice: IMSEAR (Asia Sudoriental) Tipo de estudio: Estudio observacional / Investigación cualitativa Año: 2020 Tipo del documento: Artículo