Visualizing Human Papillomavirus Conceptual Network Evolution: A Global View

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.

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.

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 twodimensional mapping method was used. The two most common co-word keywords were selected from each cluster.

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 clu