Using text analysis to quantify the similarity and evolution of scientific disciplines. Issue 1 (17th January 2018)

• Record Type: Journal Article
• Authors: Dias, Laércio; Gerlach, Martin; Scharloth, Joachim; Altmann, Eduardo G.
• Is Part Of: Royal Society open science. Volume 5:Issue 1(2018)
• Publication Date: 2018-01-17
• Subjects: science of science -- information theory -- dissimilarity measures; Science -- Periodicals; 500
• DOI: 10.1098/rsos.171545
• Languages: English
• ISSNs: 2054-5703

Abstract

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.