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

Author:

Dias Laércio1,Gerlach Martin12ORCID,Scharloth Joachim3,Altmann Eduardo G.14ORCID

Affiliation:

1. Max Planck Institute for the Physics of Complex Systems, 01187 Dresden, Germany

2. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA

3. Department of German, TU Dresden, Applied Linguistics, 01062 Dresden, Germany

4. School of Mathematics and Statistics, University of Sydney, Sydney 2006, New South Wales, Australia

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. computer science) are becoming increasingly central, but that on average the similarity between pairs of disciplines has not changed in the last decades. This suggests that tendencies of convergence (e.g. multi-disciplinarity) and divergence (e.g. specialization) of disciplines are in balance.

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

The Royal Society

Subject

Multidisciplinary

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