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Topic diversity: A discipline scheme‐free diversity measurement for journals.

Authors :
Bu, Yi
Li, Mengyang
Gu, Weiye
Huang, Win‐bin
Source :
Journal of the Association for Information Science & Technology; May2021, Vol. 72 Issue 5, p523-539, 17p, 1 Illustration, 4 Diagrams, 8 Charts, 2 Graphs
Publication Year :
2021

Abstract

Scientometrics has many citation‐based measurements for characterizing diversity, but most of these measurements depend on human‐designed categories and the granularity of discipline classifications sometimes does not allow in‐depth analysis. As such, the current paper proposes a new measurement for quantifying journals' diversity by utilizing the abstracts of scientific publications in journals, namely topic diversity (TD). Specifically, we apply a topic detection method to extract fine‐grained topics, rather than disciplines, in journals and adapt certain diversity indicators to calculate TD. Since TD only needs as inputs abstracts of publications rather than citing relationships between publications, this measurement has the potential to be widely used in scientometrics. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23301635
Volume :
72
Issue :
5
Database :
Complementary Index
Journal :
Journal of the Association for Information Science & Technology
Publication Type :
Academic Journal
Accession number :
149757587
Full Text :
https://doi.org/10.1002/asi.24433