, Volume 80, Issue 2, pp 385–406 | Cite as

Differentiating, describing, and visualizing scientific space: A novel approach to the analysis of published scientific abstracts

  • Eli M. BlattEmail author


This paper will develop and demonstrate a novel method for analyzing scientific indexes called Latent Semantic Differentiation. Using two distinct datasets comprised of scientific abstracts, it will demonstrate the procedure’s ability to identify the dominant themes, cluster the articles accordingly, visualize the results, and provide a qualitative description of each cluster. Combined, the analyses will highlight the utility of the procedure for scientific document indexing, structuring university departments, facilitating grant administration, and augmenting ongoing research on scientific citation. Because the procedure is extensible to any textual domain, there are numerous avenues for continued research both within the sciences and beyond.


Citation Analysis Latent Semantic Analysis Semantic Space Dissimilarity Matrix Dominant Theme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Akadémiai Kiadó, Budapest, Hungary 2009

Authors and Affiliations

  1. 1.Department of Anthropological SciencesStanford UniversityStanfordUSA

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