Scale‐free collaboration networks: An author name disambiguation perspective
Jinseok Kim
Journal of the Association for Information Science & Technology, 2019, vol. 70, issue 7, 685-700
Abstract:
Several studies have found that collaboration networks are scale‐free, proposing that such networks can be modeled by specific network evolution mechanisms like preferential attachment. This study argues that collaboration networks can look more or less scale‐free depending on the methods for resolving author name ambiguity in bibliographic data. Analyzing networks constructed from multiple datasets containing 3.4 M ∼ 9.6 M publication records, this study shows that collaboration networks in which author names are disambiguated by the commonly used heuristic, i.e., forename‐initial‐based name matching, tend to produce degree distributions better fitted to power‐law slopes with the typical scaling parameter (2
Date: 2019
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https://doi.org/10.1002/asi.24158
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jinfst:v:70:y:2019:i:7:p:685-700
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