Original paper

Using text analysis to quantify the similarity and evolution of scientific disciplines

Volume: 5, Issue: 1, Pages: 171545 - 171545
Published: Jan 1, 2018
Abstract
We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g....
Paper Details
Title
Using text analysis to quantify the similarity and evolution of scientific disciplines
Published Date
Jan 1, 2018
Volume
5
Issue
1
Pages
171545 - 171545
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.