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

  1. Sohrabi A, Farzami M, Mirab Samiee S, Modarressi MH. An overview on papillomaviruses as the main cause of cervical cancer. Iran J Obstet Gynecol Infertil 2015; 18(145): 14-25. [In Persian].
  2. Liao CS, Ho YS, Hsu YHE. Bibliometric analysis of human papillomavirus research in period of 1991 to 2005. Proceedings of the 37th Asia-Pacific Academic Consortium for Public Health Conference; 2005 Nov 19-23; Taipei, Taiwan.
  3. Liu G, Hu J, Wang H. A co-word analysis of digital library field in China. Scientometrics 2012; 91(1): 203-17.
  4. Lee PC, Su HN. Investigating the structure of regional innovation system research through keyword co-occurrence and social network analysis. Innovation: Management, Policy, and Practice 2010; 12(1): 26-40.
  5. Chen X, Chen J, Wu D, Xie Y, Li J. Mapping the research trends by co-word analysis based on keywords from funded project. Procedia Comput Sci 2016; 91: 547-55.
  6. Sohaili F, Shaban A, Khase A. Intellectual structure of knowledge in information behavior: A co-word analysis. Human Info Interact 2016; 2(4): 21-36. [In Persian].
  7. Ravikumar S, Agrahari A, Singh SN. Mapping the intellectual structure of scientometrics: A co-word analysis of the journal Scientometrics (20052010). Scientometrics 2015; 102(1): 929-55.
  8. 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. Med Sci Monit 2019; 25: 643-55.
  9. 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. Integr Cancer Ther 2019; 18: 1534735419846401.
  10. 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. J Med Internet Res 2019; 21(3): e12625.
  11. 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. Proceedings of the 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); 2018 Jun 28-30; Exeter, UK. p. 313-20.
  12. Lu K, Yu S, Sun D, Xing H, An J, Kong C, et al. Scientometric analysis of SIRT6 studies. Med Sci Monit 2018; 24: 8357-71.
  13. 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 Ophthalmol 2018; 18(1): 86.
  14. Lu K, Yu S, Yu M, Sun D, Huang Z, Xing H, et al. Bibliometric analysis of tumor immunotherapy studies. Med Sci Monit 2018; 24: 3405-14.
  15. Zhang W, Wang YB, Zhang XZ, Duan HM. The study of hot spots on hepatitis B dissertation based on co-word analysis in China. Stud Health Technol Inform 2017; 245: 1293.
  16. Xie P. Study of international anticancer research trends via co-word and document co-citation visualization analysis. Scientometrics 2015; 105(1): 611-22.
  17. Shokouhian M, Asemi A, Shabani A, Cheshmeh-Sohrabi M. Combined bibliometric and text-mining analysis of scientific productions in PubMed database in the field of electronic health records. Health Inf Manage 2019; 16(4):190-6. [In Persian].
  18. Emami M, Riahinia N, Soheili F. Mapping the scientific structure of medical and laboratory equipment patents in USPTO database between 1984 and 2014. Payavard 2019; 12(6): 419-32. [In Persian].
  19. Rezaei L, Mohammadi M. Scientometric analysis of Iranian scientific productions in the field of ophthalmology. Journal of Clinical and Basic Research 2018; 2(4): 23-32. [In Persian].
  20. 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. Health Inf Manage 2018; 15(3): 139-45. [In Persian].
  21. Khasseh A A, Soosaraei M, Fakhar M. Cluster analysis and mapping of Iranian researchers in the field of parasitology: With an Emphasis on the co-authoreship indicators and h index. Iran J Med Microbiol 2016; 10 (2): 63-74. [In Pesian].
  22. Hosaininasab SH, Makkizadeh F, Zalzadeh E. The thematic structure of papers on depression treatment in Pubmed from 2005 to 2014. Health Inf Manage 2016; 13(5): 347-53. [In Persian].
  23. Makkizadeh F, Hazeri A, Hosininasab S, Soheili F. Thematic analysis and scientific mapping of papers related to depression therapy in PubMed. J Health Adm 2016; 19(65): 51-63. [In Persian].
  24. Hazeri A, Goruhi M. The intellectual structure of knowledge in the field of medical knowledge management: A co-word analysis. Health Inf Manage 2019; 16(3): 136-42. [In Persian].
  25. Khazaneha M, Heaidary G, Mostafavi I. Structural analyzing of "Information Science Theories' based on co-word network analysis of articles in Web of Science database (1983-2017). Iranian Journal of Information Processing and Management 2019; 34(3): 1051-76.
  26. Danesh F, Mesrinejad F, Soheili 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 Inf Manage 2011; 8(6): 766-773. [In Persian].
  27. Lee B, Jeong YI. Mapping Korea’s national R&D domain of robot technology by using the co-word analysis. Scientometrics 2008; 77(1): 3-19.
  28. Neff MW, Corley EA. 35 years and 160,000 articles: A bibliometric exploration of the evolution of ecology. Scientometrics 2009; 80(3): 657-82.
  29. Ding Y, Chowdhury GG, Foo S. Bibliometric cartography of information retrieval research by using co-word analysis. Inform Process Manag 2001; 37(6): 817-42.
  30. Zong QJ, Shen HZ, Yuan QJ, Hu XW, Hou ZP, Deng SG. Doctoral dissertations of Library and Information Science in China: A co-word analysis. Scientometrics 2013; 94(2): 781-99.
  31. Hu CP, Hu JM, Deng SL, Liu Y. A co-word analysis of library and information science in China. Scientometrics 2013; 97(2): 369-82.
  32. Leydesdorff L, Nerghes A. Co-word maps and topic modeling: A comparison using small and medium-sized corpora (n < 1000). Journal of the Association for Information Science and Technology 2015; 68(4): 1-30.
  33. Kruskal JB. Nonmetric multidimensional scaling: A numerical method. Psychometrika 1964; 29(2): 115-29.
  34. Kruskal JB, Wish M. Multidimensional scaling. Thousand Oaks, CA: Sage Publications; 1978.
  35. Soheili F, Khasseh A, Koranian P. Thematic trends of concepts in Knowledge and Information Science based on co-word analysis in Iran. Journal of National Studies on Librarianship and Information Organization 2018; 29(2): 171-90. [In Persian].
  36. Soheili F, Khasseh A, Koranian P. Mapping intellectual structure of knowledge and information science in Iran based on co-word analysis. Iranian Journal of Information Processing and Management 2019; 34(4): 1905-38. [In Persian].