year 13, Issue 4 (September - October 2019)                   Iran J Med Microbiol 2019, 13(4): 266-278 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Danesh F, Ghavidel S. Visualizing the Clusters and Dynamics of HPV Research Area. Iran J Med Microbiol 2019; 13 (4) :266-278
URL: http://ijmm.ir/article-1-997-en.html
1- Assistant Professor, Information Management Research Group, Regional Information Center for Science and Technology (RICeST), Shiraz, Iran
2- Ph.D. Student of knowledge and Information Science, Department of knowledge and Information Science, School of Psychology and Educational Sciences, Kharazmi University, Tehran, Iran , s.ghavidel@tehranpl.ir
Full-Text [PDF 992 kb]   (1759 Downloads)     |   Abstract (HTML)  (7027 Views)
Full-Text:   (2405 Views)
Introduction

.

HPV is the most common sexually transmitted infection (STIs) that causes cervical cancer, genital warts (1), and other human cancers such as genital, oral, head and neck, skin, anus, vagina, and penis cancers (2-4). As one of the most challenging fields, many HPV kinds of research were done, where the number of international scientific publications in this area is quantitatively remarkable. Incessant researches over time have led to the formation of the scientific structure of the HPV research area in medical sciences. Most of HPV's authoritative and essential articles are indexed in internationally accredited citation databases (Web of Science and Scopus), which are used in scientometrics studies and analyses.
The research method used for scientific mapping and science measurement studies is Co-word analysis. This method studies the conceptual structure and evolution of a research field using document keywords and opens the possibility of revealing emerging clusters as well as developed clusters to predict research future for researchers (5, 6).
Given the importance of scientific papers as a suitable metric for measuring science progression, HPV results’ analyses identify strengths and weaknesses in research areas related to that. They then discover the potentialities for research work to follow and use in support of that. This issue and ultimately, the path towards greater affection is the way-to-go for the planners, decision-makers, and policymakers at the Ministry of Health and Medical Education and exclusively, for the scientific communities and the researchers. Therefore, given the strategic importance of this study and the fact that no research has been conducted so far, the necessity of doing so is deeply felt. Based on the theoretical framework explained before, the purpose of this study is to visualize the clusters and HPV dynamicity.


 

Materials and Methods

The present study is an applied one that was done using Co-word analysis, which is one of the scientific methods. This method illustrates HPV articles’ thematic structure and content by calculating the number of occurrences and hidden connections between the words and concepts in HPV. To add to this, Data was collected from the Web of Science (WoS) Citation Database. The statistical population of this study includes all articles’ keywords in the HPV subject area indexed in Web of Science (WoS) from 2014 to 2018. Worthy of mentioning, HPV specific keywords were extracted from Medical Subject Headings (MeSH).
Hierarchical clustering was performed using SPSS software (SPSS Inc., Chicago, Ill. USA). Visualization was also performed using VOSviewer software to show the high-frequency keyword structure. The threshold was set to 28 for analyzing the co-occurrence of 17278 keywords from 13249 articles.


 

Results

Investigation and Identification of Aspergillus Isolates from Rice
 

Table 1. Top 10 HPV Subject Area keywords’ ranking based on co-word analysis (2014-2018)


Table 2. Top 10 co-word pairs’ Ranking in HPV Subject Area (2014-2018)


Table 3. Density and centrality of clusters derived from the co-word analysis in HPV subject area (2014-2018)


Tablae 4. Clusters’ names in quadrants of strategic diagram



Figure 1. The network structure of high-frequency keywords in HPV subject area (2014-2018)


Figure 2. Strategic Diagram of HPV Subject Area Structure (2014-2018)

In Figure 1, the size of the nodes represents the weight of each author's scientific output, and the colors also represent the clusters formed.
A strategic diagram was designed to determine the maturity and development of clusters using concepts of centrality and density plotted on a two-dimensional grid. The x-axis of the grid shows how strongly a cluster connected to others, and the y-axis shows a cluster's development.
Clusters of 8, 13, and 1 the highest density and clusters of 9, 14, and 2, respectively, have the highest centrality (Figure 2). The origin of the strategic diagram is adjusted according to the mean centrality and density of the clusters.


 

Discussion & Conclusion

The present paper followed previous bibliometrics. So far, Research findings indicate that the most frequent keyword among HPV studies is "CERVICAL CANCER." Using a hierarchical clustering method to identify the intellectual structure of this subject area resulted in the formation of 14 subject clusters (Table 3). The plotting results of the distribution of clusters in the strategic diagram (Figure 2) indicated that the thematic areas of "HPV-induced cancers," "vaccination," "prevention", and "genital warts" are the most important emerging areas in this subject area. Last but not least are the subject areas of drug, cancer treatment, timely diagnosis, sexually transmitted diseases, and immunization of adolescent health, which expect further research in the future.
Clusters located in the second region of the strategic diagram (Figure 2) are not axial but considered developed. The third region clusters have lower centrality and density than the other clusters, so they are marginal, and at the same time, emerging and declining. The fourth region clusters present a strategic diagram that is pivotal but general and broad.
Co-word analysis is an appropriate way of discovering and mapping science, knowledge tracking, visualization, conceptual dynamics, and transformation, identifying and analyzing research fields in the subject areas by researchers that help planners and policymakers.
In the end, we suggested that another research be done in Persian scientific journals (Persian articles) with the focus of the HPV research area (using Co-word Analysis) so that the results will compare with the ones obtained in this study. Finally, researchers also suggested that in another study, all HPV publications in this subject area through the world and from the first article publication so far, do with co-occurrence analysis and the results are available to medical policymakers in the country and other international health organizations.


 

Acknowledgements

The researchers appreciate reviewers for their valuable comments.


 

Conflicts of Interest

This article is the result of an independent study conducted without organizational financial support. In the present study, the authors showed no conflict of interest.


 

Type of Study: Original Research Article | Subject: Medical Virology
Received: 2019/11/25 | Accepted: 2020/01/19 | ePublished: 2020/01/19

References
1. Braaten KP, Laufer MR. Human Papillomavirus (HPV), HPV-Related Disease, and the HPV Vaccine. Reviews in obstetrics & gynaecology(Rev Obstet Gynecol), 2008; 1(1): 2-10.
2. Khodakarami N, Hosseini S, Yavari P, Farzaneh F, Etemad K, Salehpour S, et al. Human papillomavirus infection prevalence in women referred to health clinic of Shahid Beheshti University of Medical Sciences, Tehran, Iran.Iranian Journal of Epidemiology(IJE), 2012; 7(4):35-42. ]In Persian[
3. Mobini Kesheh, M., Keyvani, H. The Prevalence of HPV Genotypes in Iranian Population: An Update. Iranian Journal of Pathology (Iran J Pathol), 2019; 14(3): 197-205. [DOI:10.30699/IJP.2019.90356.1861] [PMID] [PMCID]
4. Fakhraei F, Haghshenas MR. Human Papillomaviruses and Cancer. Journal of Mazandaran University of Medical Sciences)J Mazandaran Univ Med Sci(. 2013; 22(98):340-60. ]In Persian[
5. Hu J, Zhang Y. Research patterns and trends of Recommendation System in China using co-word analysis. Information Processing & Management. 2015; 51(4):329-39. [DOI:10.1016/j.ipm.2015.02.002]
6. Emami M, Riahinia N, Soheili F. Mapping the Scientific Structure of Medical and Laboratory Equipment Patents in USPTO database between 1984 and 2014. Journal of Payavarde Salamat. 2019; 12(6):419-32. ]In Persian[
7. Hakim JA, Schram JB, Galloway A, Morrow CD, Crowley, MR, Watts SA, et al. The Purple Sea Urchin Strongylocentrotus purpuratus demonstrates a Compartmentalization of Gut Bacterial Microbiota, Predictive Functional Attributes, and Taxonomic Co-Occurrence. Microorganisms. 2019; 7(2):35. doi: 10.3390/microorganisms7020035 [DOI:10.3390/microorganisms7020035] [PMID] [PMCID]
8. Shen L, Wang S, Dai W, Zhang Z. Detecting the Interdisciplinary Nature and Topic Hotspots of Robotics in Surgery: Social Network Analysis and Bibliometric Study. Journal of Medical Internet Research(J Med Internet Res), 2019; 21(3):e12625. [DOI:10.2196/12625] [PMID] [PMCID]
9. Yang A, Lv Q, Chen F, Wang D, Liu Y, Shi W. Identification of Recent Trends in Research on Vitamin D: A Quantitative and Co-Word Analysis. Medical Science Monitor: International Medical Journal of Experimental and Clinical Research(Med Sci Monit), 2019; 25:643-55. [DOI:10.12659/MSM.913026] [PMID] [PMCID]
10. Moral-Munoz JA, Carballo-Costa L, Herrera-Viedma E, Cobo MJ. Production trends, collaboration, and main topics of the integrative and complementary oncology research area: a bibliometric analysis. Integrative Cancer Therapies(ICT), 2019; 18:1534735419846401. [DOI:10.1177/1534735419846401] [PMID] [PMCID]
11. Huang F, Zhou Q, Leng BJ, Mao QL, Zheng LM, Zuo MZ. A bibliometric and social network analysis of pelvic organ prolapse during 2007-2016. Journal of the Chinese Medical Association(JCMA), 2017; 81(5):450-7. [DOI:10.1016/j.jcma.2017.08.012] [PMID]
12. Zhang W, Wang YB, Zhang XZ, Duan HM. The study of hot spots on hepatitis b dissertation based on co-word analysis in China. Studies in health technology and informatics(HTI), 2017; 245:1293.
13. Tarazona B, Vidal-Infer A, Tarazona-Alvarez P, Alonso-Arroyo A. Analysis of scientific production in Spanish implantology. Journal of clinical and experimental dentistry(SECIB), 2017; 9(5):e703-e11. [DOI:10.4317/jced.53718] [PMID] [PMCID]
14. Xie P. Study of international anticancer research trends via co-word and document co-citation visualization analysis. Scientometrics. 2015; 105(1): 611-22. [DOI:10.1007/s11192-015-1689-0]
15. Yao Q, Lyu P, Ma F, Yao L, Zhang S. Global informetric perspective studies on translational medical research. BMC Medical Informatics and Decision Making. 2013; 13:77. [DOI:10.1186/1472-6947-13-77] [PMID] [PMCID]
16. Zhao F, Shi B, Liu R, Zhou W, Shi D, Zhang J. Theme trends and knowledge structure on choroidal neovascularization: a quantitative and co-word analysis. BMC Ophthalmology. 2018; 18:2-11. [DOI:10.1186/s12886-018-0752-z] [PMID] [PMCID]
17. Zhang T, Chi H, Ouyang Z. Detecting research focus and research fronts in the medical big data field using co-word and co-citation analysis. In 2018 IEEE 20th International Conference on High Performance Computing and Communications; IEEE 16th International Conference on Smart City; IEEE 4th International Conference on Data Science and Systems (HPCC/ SmartCity/ DSS), Exeter, United Kingdom, 2018: 313-320. [DOI:10.1109/HPCC/SmartCity/DSS.2018.00072]
18. Lu K, Yu S, Yu M, Sun D, Xing H, An J, et al. Scientometric Analysis of SIRT6 Studies. Medical science monitor: international medical journal of experimental and clinical research(IJCEM), 2018; 24:8357-71. [DOI:10.12659/MSM.913644] [PMID] [PMCID]
19. Lu K, Yu S, Yu M, Sun D, Huang Z, Xing H, et al. Bibliometric analysis of tumor immunotherapy studies. Medical science monitor: international medical journal of experimental and clinical research(IJCEM), 2018; 24:3405-14. [DOI:10.12659/MSM.910724] [PMID] [PMCID]
20. Liao CS, Ho YS, Hsu YHE. Bibliometric analysis of human papillomavirus research in period of 1991 to 2005. Paper presented in Taipei Medical University's 94th Annual Teacher and Student Joint Academic Research Conference. Taipei, Taiwan. 2006. Poster Presentation.
21. Yousefi A, Gilvari A, Shahmirzadi T. Quantitative and Qualitative Review of Web of Science ISI Articles by Iranian Authors in Microbiology. Iranian Journal of Medical Microbiology(Iran J Med Microbiol), 2012; 6(3):59-75.
22. Baji F, Azadeh F, Parsaei-Mohammadi P, Parmah S. Mapping Intellectual Structure of Health Literacy Area Based on Co-Word Analysis in Web of Science Database during the Years 1993-2017. Isfahan University of Medical Sciences, Journal of Health Information Management (Health Inf Manag), 2018; 15(3):139-45. [In Persian[
23. Khasseh A, Fakhar M, Soosaraei M, Sadeghi S. Evaluation of scientific performance of Iranian researchers in parasitology domain in ISI databases. Iranian Journal of Medical Microbiology(Iran J Med Microbiol), 2011; 4(4):41-50. ]In Persian[
24. Khasseh AA, Soosaraei M, Fakhar M. Cluster Analysis and Mapping of Iranian Researchers in the Field of Parasitology: With an Emphasis on the Co-authorship Indicators and H Index. Iran J Med Microbiol 2016; 10(2):63-74. ]In Persian[
25. Khasseh AA, Fakhar M, Soosaraei M, Sadeghi S. Present situation of scientific productions of Iranian researchers in parasitology domain in ISI databases. Parasitology 2011; 5 (1-2): 53-65. ]In Persian[
26. Hosseininasab SH, Makkizadeh F, Zalzadeh A, Hazeri A. The Thematic Structure of Papers on Depression Treatment in PubMed from 2005 to 2014. Isfahan University of Medical Sciences, Journal of Health Information Management (Health Inf Manag), 2016; 13(5):347-53. ]In Persian[
27. Makkizadeh F, Hazeri A, Hosininasab S, Soheili F. Thematic Analysis and Scientific Mapping of Papers related to Depression Therapy in PubMed. Iran University of Medical Science, Journal of Health Administration(JHA), 2016; 19(65):51-63. ]In Persian[
28. Soheili F, Hasanzadeh P, Mousavi-Chelak A, Khasseh AA. Scientific Mapping of Chronic Heart Failure based on Co- citation Analysis. Health Information Management(Health Inf Manage), 2018; 15(5):226-32. ]In Persian[
29. Shahrabi FH, Eskrootchi R, Mohaghegh N, Hosseini AF. A Study of Scientific Collaboration in Iranian Cardiovascular Articles in Web of Science 2002- 2011. Iran University of Medical Science, Journal of Health Administration(JHA), 2014; 17(56):46-55.]In Persian[
30. Hazeri A, Goruhi M. The Intellectual Structure of Knowledge in the Field of Medical Knowledge Management: A Co-Word Analysis. Health Information Management(Health Inf Manage), 2019; 16(3):136-42. ]In Persian[
31. Shargh A, Mohammad Hassanzadeh H, Johari K, Valinejadi A, Molaei A, Amanollahi A, et al. The study of the presence of Iranian neuroscience in ISI database based on scientometric factors. Iran University of Medical Science, Journal of Health Administration(JHA), 2011; 14(44):61-70.]In Persian[
32. Mostafavi I, Osareh F, Tavakolizadeh-Ravari M. Identifying content structure of «Knowledge and Information Science (KIS)» studies based on co-word analysis of articles in «Web of Science (WoS)» database (2009-2013). Iranian Research Institute for Information Science and Technology (IRANDOC), 2017; 33(3):1285-314. [In Persian].
33. Ahmadi H, Osareh F. Co-word Analysis Concept, Definition and Application. National Studies on Librarianship and Information Organization() (NASTINFO), 2017; 28(1):125-45. ]In Persian[
34. Soheili F, Danesh F, Mesrinejad F & Isfandyari Moghadam A. Lotka's Law of Scientific Productivity and Bradford's Law of Scatter among Researchers at Isfahan University of Medical Sciences based on Web of Science Database. Health Information Management(Health Inf Manage), 2012; 8(6):766-73.]In Persian[
35. Ke W., Yunjiang X., Xiao L., Weichan L. (2013) Analysis on Current Research of Supernetwork through Knowledge Mapping Method. In: Wang M. (eds) Knowledge Science, Engineering and Management. KSEM 2013. Lecture Notes in Computer Science, vol 8041. Springer, Berlin, Heidelberg. [DOI:10.1007/978-3-642-39787-5_45]
36. Melcer E, Nguyen THD, Chen Z, Canossa A, El-Nasr MS, Isbister K. Games research today: Analyzing the academic landscape 2000-2014. The 10th International Conference on the Foundations of Digital Games. Pacific Grove, USA; June 22-25; 2015.
37. Liu GY, Hu JM, Wang HL. A co-word analysis of digital library field in China. Scientometrics, 2012; 91(1):203-217. [DOI:10.1007/s11192-011-0586-4]
38. Law J, Bauin S, Courtial J, Whittaker J. Policy and the mapping of scientific change: A co-word analysis of research into environmental acidification. Scientometrics, 1988; 14(3-4):251-64. [DOI:10.1007/BF02020078]
39. Raeeszadeh M, Karamali M. Scientific mapping of military trauma papers using co-word analysis in Medline. Journal of Military Medicine, 2018; 20(5):476-87.]In Persian[
40. Soheili F, Khasseh A, Koranian P. Thematic trends of concepts in Knowledge and Information Science based on co-word analysis in Iran. National Studies on Librarianship and Information Organization (NASTINFO), 2018; 29(2):171-90. ]In Persian[
41. Soheili F, Khasseh AA, Koranian P. Mapping Intellectual Structure of Knowledge and Information Science in Iran based on Co- word Analysis. Journal of Information Processing and Management, 2019; 34(4):1905-38. ]In Persian[
42. Soheili F, Shabani A, Khasseh A. Intellectual Structure of Knowledge in Information Behavior: A Co-Word Analysis. Human Information Interaction, 2018; 2(4):21-36. ]In Persian[

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

© 2024 CC BY-NC 4.0 | Iranian Journal of Medical Microbiology

Designed & Developed by : Yektaweb | Publisher: Farname Inc