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Using path‐based approaches to examine the dynamic structure of discipline‐level citation networks: 1997–2011
Author(s) -
Yan Erjia,
Yu Qi
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.23516
Subject(s) - citation , spanning tree , path (computing) , set (abstract data type) , tree (set theory) , computer science , critical path method , network science , minimum spanning tree , combinatorics , mathematics , theoretical computer science , complex network , library science , computer network , engineering , systems engineering , programming language
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 S copus 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 M edicine, B iochemistry, C hemistry, M aterials S cience, P hysics, and S ocial S ciences 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 M athematics to D ecision S ciences and the one from M edicine to S ocial S ciences.