Visualizing linguistic and cultural differences using Web co-link data: Research Articles
Journal of the American Society for Information Science and Technology
Visualization of the citation impact environments of scientific journals: An online mapping exercise
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Visualization of the Nordic academic web: Link analysis using social network tools
Information Processing and Management: an International Journal
Co-word analysis using the Chinese character set
Journal of the American Society for Information Science and Technology
Using field cocitation analysis to assess reciprocal and shared impact of LIS-MIS fields
Journal of the American Society for Information Science and Technology
Patent classifications as indicators of intellectual organization
Journal of the American Society for Information Science and Technology
Appropriate similarity measures for author co-citation analysis
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Visualization of the Chinese academic web based on social network analysis
Journal of Information Science
Showing the essential science structure of a scientific domain and its evolution
Information Visualization
Multi-modal social networks for modeling scientific fields
Scientometrics
The intellectual development of the technology acceptance model: A co-citation analysis
International Journal of Information Management: The Journal for Information Professionals
Journal of the American Society for Information Science and Technology
Creating a Taxonomy for Mobile Commerce Innovations Using Social Network and Cluster Analyses
International Journal of Electronic Commerce
Social semantic query expansion
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Rank-mediated collaborative tagging recommendation service using video-tag relationship prediction
Information Systems Frontiers
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Co-occurrence matrices, such as cocitation, coword, and colink matrices, have been used widely in the information sciences. However, confusion and controversy have hindered the proper statistical analysis of these data. The underlying problem, in our opinion, involved understanding the nature of various types of matrices. This article discusses the difference between a symmetrical cocitation matrix and an asymmetrical citation matrix as well as the appropriate statistical techniques that can be applied to each of these matrices, respectively. Similarity measures (such as the Pearson correlation coefficient or the cosine) should not be applied to the symmetrical cocitation matrix but can be applied to the asymmetrical citation matrix to derive the proximity matrix. The argument is illustrated with examples. The study then extends the application of co-occurrence matrices to the Web environment, in which the nature of the available data and thus data collection methods are different from those of traditional databases such as the Science Citation Index. A set of data collected with the Google Scholar search engine is analyzed by using both the traditional methods of multivariate analysis and the new visualization software Pajek, which is based on social network analysis and graph theory. © 2006 Wiley Periodicals, Inc.