A text mining and network analysis of topics and trends in major nursing research journals
Abstract Aim This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. Design Text mining and network analysis. Methods Text analysis combine...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | Nursing Open |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/nop2.2050 |
| _version_ | 1797346927729180672 |
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| author | Beratiye Oner Orhan Hakli Ferhat D. Zengul |
| author_facet | Beratiye Oner Orhan Hakli Ferhat D. Zengul |
| author_sort | Beratiye Oner |
| collection | DOAJ |
| description | Abstract Aim This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. Design Text mining and network analysis. Methods Text analysis combines automatic and manual operations to identify patterns in unstructured data. Detailed searches covering 1998–2021 were conducted in PubMed archives to collect articles from six nursing journals: Journal of Advanced Nursing, International Journal of Nursing Studies, Western Journal of Nursing Research, Nursing Research, Journal of Nursing Scholarship and Research in Nursing and Health. This study uses a four‐phase text mining and network approach, gathering text data and cleaning, preprocessing, text analysis and advanced analyses. Analyses and data visualization were performed using Endnote, JMP, Microsoft Excel, Tableau and VOSviewer versions. From six journals, 17,581 references in PubMed were combined into one EndNote file. Due to missing abstract information, 2496 references were excluded from the study. The remaining references (n = 15,085) were used for the text mining analyses. Results Eighteen subjects were determined into two main groups; research method topics and nursing research topics. The most striking topics are qualitative research, concept analysis, advanced practice in the downtrend, and literature search, statistical analysis, randomized control trials, quantitative research, nurse practice environment, risk assessment and nursing science. According to the network analysis results, nursing satisfaction and burnout and nursing practice environment are highly correlated and represent 10% of the total corpus. This study contributes in various ways to the field of nursing research enhanced by text mining. The study findings shed light on researchers becoming more aware of the latest research status, sub‐fields and trends over the years, identifying gaps and planning future research agendas. No patient or public contribution. |
| first_indexed | 2024-03-08T11:40:14Z |
| format | Article |
| id | doaj.art-4d19be9b9fae436cb6e11f3bc27123c1 |
| institution | Directory Open Access Journal |
| issn | 2054-1058 |
| language | English |
| last_indexed | 2024-03-08T11:40:14Z |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Nursing Open |
| spelling | doaj.art-4d19be9b9fae436cb6e11f3bc27123c12024-01-25T06:39:14ZengWileyNursing Open2054-10582024-01-01111n/an/a10.1002/nop2.2050A text mining and network analysis of topics and trends in major nursing research journalsBeratiye Oner0Orhan Hakli1Ferhat D. Zengul2Department of Nursing, Faculty of Health Sciences Lokman Hekim University Ankara TurkeySchool of Nursing and Health Sciences Manhattanville College Purchase New York USADepartment of Health Services Administration The University of Alabama at Birmingham Birmingham Alabama USAAbstract Aim This study is set to determine the main topics of the nursing field and to show the changing perspectives over time by analysing the abstracts of several major nursing research journals using text mining methodology. Design Text mining and network analysis. Methods Text analysis combines automatic and manual operations to identify patterns in unstructured data. Detailed searches covering 1998–2021 were conducted in PubMed archives to collect articles from six nursing journals: Journal of Advanced Nursing, International Journal of Nursing Studies, Western Journal of Nursing Research, Nursing Research, Journal of Nursing Scholarship and Research in Nursing and Health. This study uses a four‐phase text mining and network approach, gathering text data and cleaning, preprocessing, text analysis and advanced analyses. Analyses and data visualization were performed using Endnote, JMP, Microsoft Excel, Tableau and VOSviewer versions. From six journals, 17,581 references in PubMed were combined into one EndNote file. Due to missing abstract information, 2496 references were excluded from the study. The remaining references (n = 15,085) were used for the text mining analyses. Results Eighteen subjects were determined into two main groups; research method topics and nursing research topics. The most striking topics are qualitative research, concept analysis, advanced practice in the downtrend, and literature search, statistical analysis, randomized control trials, quantitative research, nurse practice environment, risk assessment and nursing science. According to the network analysis results, nursing satisfaction and burnout and nursing practice environment are highly correlated and represent 10% of the total corpus. This study contributes in various ways to the field of nursing research enhanced by text mining. The study findings shed light on researchers becoming more aware of the latest research status, sub‐fields and trends over the years, identifying gaps and planning future research agendas. No patient or public contribution.https://doi.org/10.1002/nop2.2050network analysisnursingresearchtext miningtopicstrends |
| spellingShingle | Beratiye Oner Orhan Hakli Ferhat D. Zengul A text mining and network analysis of topics and trends in major nursing research journals Nursing Open network analysis nursing research text mining topics trends |
| title | A text mining and network analysis of topics and trends in major nursing research journals |
| title_full | A text mining and network analysis of topics and trends in major nursing research journals |
| title_fullStr | A text mining and network analysis of topics and trends in major nursing research journals |
| title_full_unstemmed | A text mining and network analysis of topics and trends in major nursing research journals |
| title_short | A text mining and network analysis of topics and trends in major nursing research journals |
| title_sort | text mining and network analysis of topics and trends in major nursing research journals |
| topic | network analysis nursing research text mining topics trends |
| url | https://doi.org/10.1002/nop2.2050 |
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