Contrasting Assessments of Interdisciplinarity in Emerging Specialties

The Case of Neural Networks Research

Bibliographic Data

ID11277786
AuthorsKatherine W Mccain (0009-0003-3438-7477, Drexel University, corresponding author), P Joy Whitney (Drexel University)
Year1994
Volume15
Issue3
Pages285-306
Publication date1994-03-01
Open AccessYes
TypeARTICLE
VenueKnowledge (JOURNAL)
Journal identifiersISSN: 0164-0259 • E-ISSN: 2673-9585
PublisherSAGE Publications (PUBLISHER • US)
DOI10.1177/107554709401500303
OpenAlexW2079856011
LanguageEN
References cited21

The degree of interdiseiplinarity observed in the analysis of a research literature can depend on the analytical approach Subject assignments of highly cited journals and those frequently publishing topic-relevant articles are compared with data from a recent survey of neural networks researchers. Publication subject patterns parallel the survey results-concentrating heavily in the physical sciences and engineering-while the biological and psychological literature is more visible in citation patterns This finding may reflect both discipline-specific differences in size and publishing patterns and cross-boundary problems in the perceived usefulness of and access to published information

Bibliometrics · Citation · Citation analysis · Data science · Library science · Political science · Publishing · Subject (documents · Computer Science · Interdisciplinary Research and Collaboration · Psychology · Research Data Management Practices · scientometrics and bibliometrics research

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