Pathfinder associative networks: studies in knowledge organization
Pathfinder associative networks: studies in knowledge organization
Self-organizing maps
Visualizing science by citation mapping
Journal of the American Society for Information Science
Domain visualization using VxInsight for science and technology management
Journal of the American Society for Information Science and Technology
Visualizing and tracking the growth of competing paradigms: two case studies
Journal of the American Society for Information Science and Technology
The chasms of CSCW: a citation graph analysis of the CSCW conference
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Knowledge map of information science: Research Articles
Journal of the American Society for Information Science and Technology
Topological analysis of citation networks to discover the future core articles: Research Articles
Journal of the American Society for Information Science and Technology
Finding cohesive clusters for analyzing knowledge communities
Knowledge and Information Systems
Visual overviews for discovering key papers and influences across research fronts
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Analyzing knowledge communities using foreground and background clusters
ACM Transactions on Knowledge Discovery from Data (TKDD)
Showing the essential science structure of a scientific domain and its evolution
Information Visualization
The intellectual development of the technology acceptance model: A co-citation analysis
International Journal of Information Management: The Journal for Information Professionals
Link prediction in citation networks
Journal of the American Society for Information Science and Technology
Journal of Information Science
Exploring health information technology education: An analysis of the research
Technology and Health Care
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Can maps of science tell us anything about paradigms? The author reviews his earlier work on this question, including Kuhn's reaction to it. Kuhn's view of the role of bibliometrics differs substantially from the kinds of reinterpretations of paradigms that information scientists are currently advocating. But these reinterpretations are necessary if his theory will ever be empirically tested, and further progress is to be made in understanding the growth of scientific knowledge. A new Web tool is discussed that highlights rapidly changing specialties that may lead to new ways of monitoring revolutionary change in real time. It is suggested that revolutionary and normal science be seen as extremes on a continuum of rates of change rather than, as Kuhn originally asserted, as an all or none proposition.