Evaluating the nursing academicians in Turkey in the scope of Web of Science: scientometrics of original articles


Damar H. T., Bilik Ö., Özdağoğlu G., Özdağoğlu A., Damar M.

SCIENTOMETRICS, vol.115, no.1, pp.539-562, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 115 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.1007/s11192-018-2641-x
  • Journal Name: SCIENTOMETRICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus
  • Page Numbers: pp.539-562
  • Keywords: Nursing research, Scientometrics, Turkish nursing academicians, Publication performance, Web of Science, Text analytics, Citation mining, BIBLIOMETRIC ANALYSIS, IMPACT FACTORS, JOURNALS, INFORMETRICS, HISTORY, TRENDS, FIELD
  • Dokuz Eylül University Affiliated: Yes

Abstract

Scientometrics, bibliometrics, webometrics, and informetrics are specific research fields that cover statistical analyses of a particular research field which summarize the information related to topics handled during a particular time period; authors, citations and their demographic characteristics; network relationships among the authors. This study, which can be classified in both scientometrics and webometrics, aims at revealing the current situation and the performance of academicians working in the nursing field in Turkey through basic and advanced data analyses conducted on their published original articles in a Web of Science. The raw data including the details of the publications were first parsed into a novel database where the authors' affiliations were stored with respect to the data obtained from the website of the Turkish Higher Education Council. Over the integrated database, particular tables were generated to show the summary of the academic and demographic distributions of the publications. Specific statistical tests were applied to reveal the relationships and differences. Furthermore, analyses were carried out within text mining on authors, titles, keywords, abstracts, and references in order to examine the contents and references of the articles included in the data set to reveal keyword densities, particular topics, and co-authorship and citation networks. One of the challenging part of this research was the dataset collection and cleansing process, because of the special letters of Turkish Language, e.g. double dagger, AY, o, u. This issue was resolved when the representation pattern of the letters were discovered and queries were executed with respect to those patterns. This study has provided meaningful findings to both the field of nursing the scientometrics, since it reveals the academic performance in a particular field and systematically presents the current situation by examining the relevant studies in an analytical perspective.