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

Laércio Dias, Martin Gerlach, Joachim Scharloth, Eduardo G. Altmann*

*この研究の対応する著者

研究成果: Article査読

28 被引用数 (Scopus)

抄録

We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20M 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.

本文言語English
論文番号171545
ジャーナルRoyal Society Open Science
5
1
DOI
出版ステータスPublished - 2018 1月 17
外部発表はい

ASJC Scopus subject areas

  • 一般

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