Neural embeddings of scholarly periodicals reveal complex disciplinary organizations

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

10 Scopus Citations
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Author(s)

  • Hao Peng
  • Qing Ke
  • Ceren Budak
  • Daniel M. Romero
  • Yong-Yeol Ahn

Detail(s)

Original languageEnglish
Article numbereabb9004
Journal / PublicationScience Advances
Volume7
Issue number17
Online published23 Apr 2021
Publication statusPublished - Apr 2021
Externally publishedYes

Link(s)

Abstract

Understanding the structure of knowledge domains is one of the foundational challenges in the science of science. Here, we propose a neural embedding technique that leverages the information contained in the citation network to obtain continuous vector representations of scientific periodicals. We demonstrate that our periodical embeddings encode nuanced relationships between periodicals and the complex disciplinary and interdisciplinary structure of science, allowing us to make cross-disciplinary analogies between periodicals. Furthermore, we show that the embeddings capture meaningful “axes” that encompass knowledge domains, such as an axis from “soft” to “hard” sciences or from “social” to “biological” sciences, which allow us to quantitatively ground periodicals on a given dimension. By offering novel quantification in the science of science, our framework may, in turn, facilitate the study of how knowledge is created and organized.

Research Area(s)

Citation Format(s)

Neural embeddings of scholarly periodicals reveal complex disciplinary organizations. / Peng, Hao; Ke, Qing; Budak, Ceren; Romero, Daniel M.; Ahn, Yong-Yeol.

In: Science Advances, Vol. 7, No. 17, eabb9004, 04.2021.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

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