Search Results

You are looking at 1 - 2 of 2 items for

  • Author or Editor: Lei Cui x
  • All content x
Clear All Modify Search

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.

Restricted access

Abstract

Objective  This paper aimed to examine the reliability of co-citation clustering analysis in representing the research history of subject by comparing the results from co-citation clustering analysis with a review written by authorities. Methods  Firstly, the treatment of traumatic spinal cord injury was chosen as an investigated subject to be retrieved the resource articles and their references were downloaded from Science Citation Index CD-ROM between 1992 and 2002. Then, the highly cited papers were arranged chronologically and clustered with the method of co-citation clustering. After mapping the time line visualization, the history and structure of treatment of spinal cord injury were presented clearly. At last, the results and the review were compared according the time period, and then the recall and the precision were calculated. Results  The recall was 37.5%, and the precision was 54.5%. The research history of traumatic spinal cord injury treatment analyzed by co-citation clustering was nearly consistent with authoritative review, although some clusters had shorter period than which was summarized by professionals. Conclusion  This paper concluded that co-citation clustering analysis was a useful method in representing the research history of subject, especially for the information researchers, who do not have enough professional knowledge. Its demerit of low recall could be offset by combination this method with other analytic techniques.

Restricted access