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Using path‐based approaches to examine the dynamic structure of discipline‐level citation networks: 1997–2011
Journal article   Open access

Using path‐based approaches to examine the dynamic structure of discipline‐level citation networks: 1997–2011

Erjia Yan and Qi Yu
Journal of the Association for Information Science and Technology, v 67(8), pp 1943-1955
Aug 2016
url
https://doi.org/10.1002/asi.23516View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze) Open

Abstract

informetrics
The objective of this paper is to identify the dynamic structure of several time‐dependent, discipline‐level citation networks through a path‐based method. A network data set is prepared that comprises 27 subjects and their citations aggregated from more than 27,000 journals and proceedings indexed in the Scopus database. A maximum spanning tree method is employed to extract paths in the weighted, directed, and cyclic networks. This paper finds that subjects such as Medicine, Biochemistry, Chemistry, Materials Science, Physics, and Social Sciences are the ones with multiple branches in the spanning tree. This paper also finds that most paths connect science, technology, engineering, and mathematics (STEM) fields; 2 critical paths connecting STEM and non‐STEM fields are the one from Mathematics to Decision Sciences and the one from Medicine to Social Sciences.

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Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Information Systems
Information Science & Library Science
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