Randomization tests
Visualizing a discipline: an author co-citation analysis of information science, 1972–1995
Journal of the American Society for Information Science
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Author cocitation analysis and Pearson's r
Journal of the American Society for Information Science and Technology
Information Theory, Inference & Learning Algorithms
Information Theory, Inference & Learning Algorithms
Journal of the American Society for Information Science and Technology - Special issue: Part II: Information seeking research
Letter to the editor: Pearson's r and author cocitation analysis: a commentary on the controversy
Journal of the American Society for Information Science and Technology
Similarity measures, author cocitation analysis, and information theory: Brief Communication
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Towards all-author co-citation analysis
Information Processing and Management: an International Journal - Special issue: Informetrics
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Some comments on the question whether co-occurrence data should be normalized
Journal of the American Society for Information Science and Technology
Should co-occurrence data be normalized? A rejoinder: Letter to Editor
Journal of the American Society for Information Science and Technology
Multi-modal social networks for modeling scientific fields
Scientometrics
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We provide in this article a number of new insights into the methodological discussion about author co-citation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors' co-citation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. We show by means of an example that the choice of an appropriate similarity measure has a high practical relevance. Finally, we discuss the use of similarity measures for statistical inference. © 2008 Wiley Periodicals, Inc.