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Disciplinary knowledge production and diffusion in science
Author(s) -
Yan Erjia
Publication year - 2016
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.23541
Subject(s) - citation , discipline , scopus , knowledge production , citation impact , knowledge flow , citation analysis , computer science , production (economics) , knowledge management , data science , econometrics , sociology , social science , library science , economics , political science , medline , microeconomics , law
This study examines patterns of dynamic disciplinary knowledge production and diffusion. It uses a citation data set of Scopus‐indexed journals and proceedings. The journal‐level citation data set is aggregated into 27 subject areas and these subjects are selected as the unit of analysis. A 3‐step approach is employed: the first step examines disciplines' citation characteristics through scientific trading dimensions; the second step analyzes citation flows between pairs of disciplines; and the third step uses egocentric citation networks to assess individual disciplines' citation flow diversity through S hannon entropy. The results show that measured by scientific impact, the subjects of C hemical E ngineering, E nergy, and E nvironmental S cience have the fastest growth. Furthermore, most subjects are carrying out more diversified knowledge trading practices by importing higher volumes of knowledge from a greater number of subjects. The study also finds that the growth rates of disciplinary citations align with the growth rates of global research and development ( R & D ) expenditures, thus providing evidence to support the impact of R & D expenditures on knowledge production.