Bibliographic data: a different analysis perspective


Abstract


A bibliografic record, related to a product, is composed by different information: authors, year, source, publisher, keywords, abstract, citations and so on. Citations usually have a central role in bibliometric analysis. The study of textual information could be a different analysis perspective. The idea is that documents are mixture of latent topics, where a topic is a probability distribution over words. In this paper we try to show how the scientificic productivity of a research group can be described using topic models. Moreover, for the same sample, we test if the other bibliometric measures follow the known distribution laws.

DOI Code: 10.1285/i20705948v5n3p353

Keywords: Text mining; topic models; bibliometrics; distribution laws

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