Properties of pathfinder networks
Pathfinder associative networks
Visualizing a discipline: an author co-citation analysis of information science, 1972–1995
Journal of the American Society for Information Science
Self-Organizing Maps
Real-time author co-citation mapping for online searching
Information Processing and Management: an International Journal
A new approach for detecting scientific specialties from raw cocitation networks
Journal of the American Society for Information Science and Technology
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A key process of any citation analysis study is to map the coded citation data from a high-dimensional dataset to a lower dimensional one while detecting the groups, clusters, patterns or other features of the citation relationships. Over the years, many methods have been used in various studies, including multi-dimensional scaling, Pathfinder networks, Kohonen's self-organizing mapping, etc. Many of these methods are fundamentally different, but their results are similar and comparable. In this study, we selected and applied four of the mapping methods to the same dataset, the author co-citation matrix of the top 100 highly cited information scientists. The results of the different mapping methods provide interesting comparisons among the different mapping algorithms as well as the different views of the dataset.