  The organization and evolution of science has recently become itself an
object of scientific quantitative investigation, thanks to the wealth of
information that can be extracted from scientific documents, such as citations
between papers and co-authorship between researchers. However, only few studies
have focused on the concepts that characterize full documents and that can be
extracted and analyzed, revealing the deeper organization of scientific
knowledge. Unfortunately, several concepts can be so common across documents
that they hinder the emergence of the underlying topical structure of the
document corpus, because they give rise to a large amount of spurious and
trivial relations among documents. To identify and remove common concepts, we
introduce a method to gauge their relevance according to an objective
information-theoretic measure related to the statistics of their occurrence
across the document corpus. After progressively removing concepts that,
according to this metric, can be considered as generic, we find that the topic
organization displays a correspondingly more refined structure.

Physics and Society;Computation and Language;Digital Libraries;Social and Information Networks