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Co-citations in context: Disciplinary heterogeneity is relevant

Authors :
Bradley, James
Devarakonda, Sitaram
Davey, Avon
Korobskiy, Dmitriy
Liu, Siyu
Lakhdar-Hamina, Djamil
Warnow, Tandy
Chacko, George
Source :
Quantitative Science Studies, Vol 1, Iss 1, Pp 264-276 (2020)
Publication Year :
2020
Publisher :
The MIT Press, 2020.

Abstract

Citation analysis of the scientific literature has been used to study and define disciplinary boundaries, to trace the dissemination of knowledge, and to estimate impact. Co-citation, the frequency with which pairs of publications are cited, provides insight into how documents relate to each other and across fields. Co-citation analysis has been used to characterize combinations of prior work as conventional or innovative and to derive features of highly cited publications. Given the organization of science into disciplines, a key question is the sensitivity of such analyses to frame of reference. Our study examines this question using semantically themed citation networks. We observe that trends reported to be true across the scientific literature do not hold for focused citation networks, and we conclude that inferring novelty using co-citation analysis and random graph models benefits from disciplinary context.

Subjects

Subjects :
Science (General)
Q1-390

Details

Language :
English
ISSN :
26413337
Volume :
1
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Quantitative Science Studies
Publication Type :
Academic Journal
Accession number :
edsdoj.23ad476e8bcf4389a77f8ea55957c5bc
Document Type :
article
Full Text :
https://doi.org/10.1162/qss_a_00007