A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Software engineering as seen through its research literature: a study in co-word analysis
Journal of the American Society for Information Science
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Bibliometric cartography of information retrieval research by using co-word analysis
Information Processing and Management: an International Journal
Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Journal of the American Society for Information Science and Technology
The Journal of Machine Learning Research
Author cocitation analysis and Pearson's r
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
How to normalize cooccurrence data? An analysis of some well-known similarity measures
Journal of the American Society for Information Science and Technology
Learning author-topic models from text corpora
ACM Transactions on Information Systems (TOIS)
Co-authorship networks in the digital library research community
Information Processing and Management: an International Journal - Special issue: Infometrics
Journal of the American Society for Information Science and Technology
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
Journal of the American Society for Information Science and Technology
Topic-based PageRank on author cocitation networks
Journal of the American Society for Information Science and Technology
Journal of the American Society for Information Science and Technology
Combining contents and citations for scientific document classification
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
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Relationships between authors based on characteristics of published literature have been studied for decades. Author cocitation analysis using mapping techniques has been most frequently used to study how closely two authors are thought to be in intellectual space based on how members of the research community co-cite their works. Other approaches exist to study author relatedness based more directly on the text of their published works. In this study we present static and dynamic word-based approaches using vector space modeling, as well as a topic-based approach based on latent Dirichlet allocation for mapping author research relatedness. Vector space modeling is used to define an author space consisting of works by a given author. Outcomes for the two word-based approaches and a topic-based approach for 50 prolific authors in library and information science are compared with more traditional author cocitation analysis using multidimensional scaling and hierarchical cluster analysis. The two word-based approaches produced similar outcomes except where two authors were frequent co-authors for the majority of their articles. The topic-based approach produced the most distinctive map. © 2012 Wiley Periodicals, Inc.