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Visualizing Human Papillomavirus Conceptual Network Evolution: A Global View

Document Type : Original Article

Authors

1 Assistant Professor, Knowledge and Information Science, Department of Information Management Research, Regional Information Center for Science and Technology, Shiraz, Iran

2 PhD Student, Knowledge and Information Science, Department of Knowledge and Information Science, School of Psychology and Education, Kharazmi University, Tehran, Iran

Abstract

Introduction: Co-word analysis is used to identify the intellectual structure governing the research field and uncover the research aspects. The main purpose of this study is to visualize the human papillomavirus (HPV) conceptual network.Methods: The 17278 keywords extracted from the 13249 articles on the HPV indexed in the Web of Science (WoS) database from 2014-2018 constituted the study samples. The Medical Subject Headings (MeSH) was used to identify the keywords to determine the search strategy.Results: 126 repeated keywords with high frequency were identified, the most frequent of which was cervical cancer. Hierarchical clustering of findings led the researchers to 14 subject clusters, the biggest of which being HPV symptoms and disease with 30 keywords. In order to gain a more comprehensive insight into the structure of the studied subjects, the two-dimensional mapping method was used. The two most common co-word keywords were selected from each cluster.Conclusion: As suitable tool for identifying the most relevant subjects and concepts, co-word occurrence analysis could discover the intellectual structure of the HPV research field. Regarding the frequency of clusters and keywords, HPV research has a close connection with general medical research fields such as prevention and treatment.

Keywords

References
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Health Information Management
Volume 16, Issue 6 - Serial Number 6
December 2020
Pages 301-307
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