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Integration of three visualization methods based on co-word analysis

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Abstract

Visualization of subject structure based on co-word analysis is used to explore the concept network and developmental tendency in certain field. There are many visualization methods for co-word analysis. However, integration of results by different methods is rarely reported. This article addresses the knowledge gap in this field of study. We compare three visualization methods: Cluster tree, strategy diagram and social network maps, and integrate different results together to one result through co-word analysis of medical informatics. The three visualization methods have their own character: cluster trees show the subject structure, strategic diagrams reveal the importance of topic themes in the structure, and social network maps interpret the internal relationship among themes. Integration of different visualization results to one more readable map complements each other. And it is helpful for researchers to get the concept network and developmental tendency in a certain field.

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References

  • Amini, M. -R., & Goutte, C. (2010). A co-classification approach to learning from multilingual corpora. Machine Learning, 79(1–2), 105–121.

    Article  Google Scholar 

  • Borner, K., Chen, C., & Boyack, K. W. (2003). Visualizing knowledge domains. Annual Review of Information Science and Technology, 37(1), 179–255.

    Google Scholar 

  • Börner, K., Sanyal, S., & Vespignani, A. (2007). Network science. Annual Review of Information Science and Technology, 41, 60.

    Google Scholar 

  • Chen, C. M. (2005). Searching for clinical evidence in CiteSpace. AMIA Annual Symposium Proceedings, 121–125.

  • Chen, C. (2006). CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for Information Science & Technology, 57(3), 359–377.

    Article  Google Scholar 

  • Cottrill, C. A., Rogers, E. M., & Mills, T. (2010). Co-citation analysis of the scientific literature of innovation research traditions diffusion of innovations and technology transfer. Journal of Information Science, 36(3), 383–400.

    Article  Google Scholar 

  • Creswick, N., & Westbrook, J. I. (2010). Social network analysis of medication advice-seeking interactions among staff in an Australian hospital. International Journal of Medical Informatics, 79(6), 116–125.

    Article  Google Scholar 

  • Cui, L., Liu, W., & Yan, L. (2008). Development of a text mining system based on the co-occurrence of bibliographic items in literature databases. New Technology of Library and Information Service, 24(8), 70–75.

    Google Scholar 

  • Ding, Y., Chowdhury, G. G., & Foo, S. (2001). Bibliometric cartography of information retrieval research by using co-word analysis. Information Processing & Management, 37(6), 817–842.

    Article  MATH  Google Scholar 

  • Donohue, J. C. (Ed.). (1973). Understanding scientific literatures-A bibliometric approach. Cambridge: The MIT Press.

    Google Scholar 

  • Everett, M. (Ed.). (2003). Social network analysis. Essex: Textbook at Essex Summer School in SSDA.

    Google Scholar 

  • Hou, H., Liu, Z., & Chen, Y. (2006). Mapping of science studies: The trend of research fronts. Science Research Management, 27(3), 90–96.

    Google Scholar 

  • Kostoff, R. N., Stump, J. A., Johnson, D., Murday, J. S., Lau, C. G. Y., & Tolles, W. M. (2006). The structure and infrastructure of the global nanotechnology literature. Journal of Nanoparticle Research, 8(3), 301–321.

    Article  Google Scholar 

  • Larsen, T. J., & Levine, L. (2005). Searching for management information systems: coherence and change in the discipline. Information Systems Journal, 15(4), 357–381.

    Article  Google Scholar 

  • Law, J., Bauin, S., Courtial, J.-P., & Whittaker, J. (1988). Policy and the mapping of scientific changer: A co-word analysis of research into environmental acidification. Scientometrics, 14(3–4), 251–264.

    Article  Google Scholar 

  • Lee, B., & Jeong, Y. -I. (2008). Mapping Korea’s national R&D domain of robot technology by using the co-word analysis. Scientometrics, 77(1), 17.

    Article  Google Scholar 

  • Lin, S. M., McConnell, P., & Johnson, K. F. (2004). MedlineR: an open source library in R for medline literature data mining. Bioinformatics, 20(8), 3659–3661.

    Article  Google Scholar 

  • Musgrove, P. B., Binns, R., Page-Kennedy, T., & Thelwall, M. (2003). A method for identifying clusters in sets of interlinking web spaces. Scientometrics, 58(3), 657–672.

    Article  Google Scholar 

  • Noyons, C. (2005). Science maps within a science policy context. Handbook of Quantitative Science and Technology Research, 237–255.

  • Ponzi, L. J. (Ed.). (2003). The evolution and intellectual development of knowledge management. New York: Long Island University.

    Google Scholar 

  • Scott, J., Tallia, A., & Crosson, J. C. (2005). Social network analysis as an analytic tool for interaction patterns in primary care practices. Annals of Family Medicine, 3(5), 443–448.

    Article  Google Scholar 

  • Van Raan, A. F. J., & Tijssen, R. J. W. (1993). The neural net of neural network research. Scientometrics, 26(1), 169–172.

    Article  Google Scholar 

  • Vitevitch, M. S. (2008). What can graph theory tell us about word learning and lexical retrieval? Journal of Speech Language and Hearing Research, 51(2), 408–422.

    Article  Google Scholar 

  • Wagner, C. S., & Leydesdorff, L. (2005). Mapping the network of global science: comparing international co-authorships from 1990 to 2000. International Journal of Technology and Globalisation, 1(2), 185–208.

    Article  Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Google Scholar 

Download references

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Correspondence to Lei Cui.

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Yang, Y., Wu, M. & Cui, L. Integration of three visualization methods based on co-word analysis. Scientometrics 90, 659–673 (2012). https://doi.org/10.1007/s11192-011-0541-4

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